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Public Health Nutrition: 12(10), 1938–1945 doi:10.1017/S1368980009004881
Screen time and adiposity in adolescents in Mexico
Martı
´n Lajous
1,2
, Jorge Chavarro
2,3
, Karen E Peterson
3,4
, Bernardo Herna
´ndez-Prado
1
,
Aurelio Cruz-Valde
´z
1
, Mauricio Herna
´ndez-A
´vila
1
and Eduardo Lazcano-Ponce
1,
*
1
Center for Population Health Research, National Institute of Public Health, Av. Universidad 655, Col. Santa
Maria Ahuacatitla
´n, CP 62508, Cuernavaca, Morelos, Mexico:
2
Department of Epidemiology, Harvard School
of Public Health, Boston, MA, USA:
3
Department of Nutrition, Harvard School of Public Health, Boston, MA,
USA:
4
Department of Society, Human Development and Health, Harvard School of Public Health, Boston, MA, USA
Submitted 22 November 2007: Accepted 18 November 2008: First published online 23 February 2009
Abstract
Objective: To assess the association of time spent viewing television, videos
and video games with measures of fat mass (BMI) and distribution (triceps and
subscapular skinfold thicknesses (TSF, SSF)).
Design: Cross-sectional validated survey, self-administered to students to assess
screen time (television, videos and video games) and lifestyle variables. Trained
personnel obtained anthropometry. The association of screen time with fat mass
and distribution, stratified by sex, was modelled with multivariable linear
regression analysis, adjusting for potential confounders and correlation of
observations within schools.
Setting: State of Morelos, Mexico.
Subjects: Males (n3519) and females (n5613) aged 11 to 18 years attending urban
and rural schools in Morelos.
Results: In males, screen time of .5h/d compared with ,2 h/d was significantly
associated with a 0?13 (95 % CI 0?04, 0?23) higher BMI Z-score, 0?73 mm (95 % CI 0?24,
1?22) higher SSF and 1?08 mm (95 % CI 0?36, 1?81) higher TSF. The positive association
of screen time with SSF was strongest in males aged 11–12 years. Sexual maturity
appeared to modify the association in females; a positive association between screen
time and SSF was observed in those who had not undergone menarche (Pfor
trend 50?04) but not among sexually mature females (Pfor trend 50?75).
Conclusion: Screen time is associated with fat mass and distribution among
adolescent males in Mexico. Maturational tempo appears to affect the relationship
of screen time with adiposity in boys and girls. Findings suggest that obesity
preventive interventions in the Mexican context should explore strategies to
reduce screen time among youths in early adolescence.
Keywords
Body mass index
Triceps skinfold
Subscapular skinfold
Television viewing
Screen time
Consistent with worldwide trends, the prevalence of
obesity in Mexico is increasing
(1)
. Between 1999 and
2006, the proportion of adults who were overweight or
obese increased from 67 to 72 % in women and from 61 to
67 % in men
(2,3)
. Using international cut-off points, the
prevalence of obesity in 1999 was 5?5 % in pre-school
children and 19?5 % in children aged 5 to 11 years
(4)
.
Understanding behavioural determinants of youth
obesity trends is essential to developing effective public
health approaches to prevention and control in different
country contexts. In observational studies, television
viewing in children and adolescents has been associated
with increased adiposity and obesity
(5–9)
and predicted
high BMI, smoking, low cardiorespiratory fitness and high
serum cholesterol in early adulthood
(10)
. Randomized
trials to limit television time and computer use among
children in the USA resulted in a significant reduction of
BMI
(11)
and lower BMI, triceps skinfold thickness (TSF),
waist circumference and waist:hip ratio
(12)
. Decreases in
television viewing also mediated the effect of a middle-
school, interdisciplinary curriculum on obesity (classified
as BMI and TSF .85th percentile) in young adolescent
girls
(13)
.
Previous studies of the association of screen time with
youth obesity have inconsistently assessed the use of
media other than television. Limited information on
demographic, lifestyle and reproductive factors for
chronic disease also may undermine the interpretability
of results due to confounding by unmeasured variables.
Furthermore, assessment of fat distribution in early pub-
erty through skinfold thickness in addition to fat mass
may unveil additional insights on chronic disease risk in
Mexican youths. In the present study, we examined the
association between time spent viewing television, videos
*Corresponding author: Email elazcano@correo.insp.mx rThe Authors 2009
and video games and anthropometric measures of fat
mass and distribution in a large survey of adolescents in
the State of Morelos in Mexico.
Research methods and procedures
Study population
The data presented here derive from a large, representative
survey conducted in 1999 to assess the prevalence of
chronic disease risk factors in youths in the State of Morelos,
Mexico. The methods are described elsewhere
(14)
. Briefly,
the study included a sample of youths aged 11 to 24 years
attending public junior high schools, high schools and the
State university. The sampling unit was the school. The
study population comprised 13 293 individuals, 56% of
whom were female. The response rate was 98?6%. An
imbalance between males and females in the sample was
due to both an underlying distribution that favours females
and a higher response rate in this group. Signed informed
consent forms were obtained separately from the study
participants and from their parents prior to collection of
information. Participants were asked to complete a self-
administered questionnaire on general lifestyle, frequency
of food consumption, physical activity, drug use and
health-care use. The survey was conducted in classrooms
during school hours; anthropometry on all participants
was obtained by trained staff in school settings. The study
was approved by the Human Subjects Committee of the
National Institute of Public Health of Mexico.
Eligible individuals for the current analysis were 11 to 18
years of age with complete questionnaire and anthropo-
metric information. We excluded young adults between
19 and 24 years of age because we considered adolescence
the developmental stage most biologically relevant to the
emergence of chronic disease in early adulthood. To
reduce potential confounding by underlying conditions
associated with disability and related inactivity, we
excluded underweight individuals, defined as being
below the 15th percentile for BMI
(15)
and for TSF
(16,17)
.
The final analytic sample comprised 9132 participants,
62 % of whom were female. This sub-sample did not
differ significantly from the original sample with respect
to major sociodemographic characteristics.
Data collection
Screen viewing and physical activity were measured
using a questionnaire validated in Mexican youths
(18)
.
Individuals were asked about their usual daily hours
viewing television, videos and video games (never, ,1,
1–2, 2–3, 3–4, 4–5, 6–7 or .7) on weekdays, Saturdays
and Sundays. Computer use was not collected because
home computer use is uncommon in this population.
Eighteen per cent of participants reported total daily
screen time greater than 12 h. A weighted average of
hours of screen viewing (weekdays, Saturday and Sunday)
was computed to obtain an overall average screen time.
We categorized screen time as ,2, 2–2?9, 3–3?9, 4–4?9
and $5 h/d in order to limit the error introduced by
multitasking (e.g. playing video games while watching
television) and the influence of outliers. Total television
and total video/video games were similarly categorized.
A weighted average of hours of inactivity was calculated
using weekday and weekend hours of sitting down, using
private or public transportation, doing homework and
sleeping. The questionnaire also included eleven items to
evaluate weekly hours of recreational physical activities
(never, ,0?5, 0?5–2, 2–4 and 4–6)
(17)
. Weekly expenditure
of metabolic equivalents (MET) of moderate and vigorous
physical activity was estimated by multiplying the
responses to questions by the activity-specific energy
expenditure as reported by Ainsworth et al.
(19)
. Energy
intake was estimated from a 103-item FFQ adapted from
a questionnaire validated for the Mexican adult popula-
tion
(20)
. Socio-economic status (SES) was assessed using
an index derived from a principal components analysis
for the Mexican population that includes number of
rooms in the house, people living in the household,
municipal services, sanitary conditions, educational level
of the mother’s most recent sexual partner, and owner-
ship of home, car, television, video recorder and tele-
phone. Three categories were constructed using tertiles of
the principal component score
(21)
.
Height, weight, TSF and subscapular skinfold thickness
(SSF) were measured using standardized procedures by
trained personnel. Height and weight were measured
using daily gauged portable stadiometers and portable
Tanita scales (Tanita Corp., Itabashini-Ku, Tokyo, Japan),
respectively. For skinfolds, the average of three mea-
surements using Lange callipers (Beta Technology, Inc.,
Santa Cruz, CA, USA) was used and expressed in milli-
metres. BMI was calculated as weight/height
2
(kg/m
2
)
using the measured anthropometric data. Age- and sex-
specific standard deviation scores (Z-scores) for BMI were
calculated using the 2000 guidelines of the Centers for
Disease Control and Prevention
(15)
. The age-specific cut-
off points for overweight and obesity of the International
Obesity Taskforce were used to estimate their prevalence.
These cut-off points use an international reference
population comprising children and adolescents from six
different countries
(22)
. These cut-offs were used for
descriptive purposes only, to permit comparisons of BMI
distribution with other countries.
Statistical analysis
We analysed females and males separately. Means and
standard deviations were estimated for screen viewing
time within categories of selected participant character-
istics and the distribution was compared across categories
with the Kruskal–Wallis test. For ordinal predictors,
we tested for linearity using linear regression. Next, we
constructed linear regression models to explore the
Screen time and adiposity in adolescents 1939
association of BMI Z-scores, TSF and SSF with screen time
using the SAS SURVEYREG procedure to account for the
non-independence of the observations given that the
primary sampling unit was the school and that observa-
tions within schools may be correlated (SAS version 8;
SAS Institute Inc., Cary, NC, USA). Potential confounders
of these associations considered in the multivariable
model included age, height, SES tertile, single-parent
family, birth in a hospital, father’s educational level,
mother’s educational level, family income, family health
insurance, weekly MET of moderate-to-vigorous physical
activity, daily hours of inactivity excluding screen time,
type of community (urban, suburban, rural), total energy
intake, diagnosis of asthma, dieting and frequency of
restaurant dining. Given the rapid change in adipose tis-
sue distribution, linear growth, metabolic and hormonal
environment during adolescence, we hypothesized that
age would modify the relationship of screen time with
adiposity. Based on the results of this analysis we con-
sidered post hoc sexual maturity as another potential
effect modifier. Sexual maturity was also considered a
confounder. Females who had undergone menarche and
males who reported having had an ejaculation were
considered sexually mature. We also considered living in
a rural environment and moderate-to-vigorous physical
activity to be modifiers of this relationship because phy-
sical activity affects adipose tissue and individuals in a
rural environment may be more active. Results are pre-
sented as age-adjusted and multivariate-adjusted.
Results
Table 1 shows the characteristics of the study population.
Male adolescents reported a higher energy intake and
greater MET of moderate and vigorous physical activities
than females. After transforming questionnaire categories
on media use to continuous variables, among males, a
greater amount of total daily hours of screen time was
spent watching television (2?7(
SD 1?9) h) than watching
videos (1?9(
SD 1?8) h) and playing video games (1?8(SD
1?9) h). On average, females spent 2?8(SD 1?9) h watching
television, 1?6(
SD 1?8) h on videos and 1?3(SD 1?8) h
playing video games every day. Menarche was reported
by 5229 (93?2 %) of female participants. The prevalence
of obesity was slightly higher in males; approximately
one-third of males and females were overweight.
Total daily screen time by different sociodemographic
characteristics is described in Table 2. Significant differences
in the mean daily screen time were observed for age, type
of community, SES and medical insurance in males and
females (P,0?01). Adolescent girls who reported they were
dieting to lose weight reported significantly less screen time
Table 1 Characteristics of 9132 Mexican adolescents from public schools in Morelos, Mexico (1999)
Males (n3519) Females (n5613)
Variable Mean SD Mean SD
Age (years) 13?81?813?91?7
Energy intake (kJ/d) 17 975 5306 16 670 5332
Moderate-to-vigorous physical activity (MET/week) 110 42 90?847?3
Total screen time* (h/d) 5?93?05?43?0
BMI (Z-score) 0?48 0?97 0?58 0?84
Triceps skinfold thickness (mm) 14 7 22 7
Subscapular skinfold thickness (mm) 11 5 15 5
Obesity-(%) 6?76?0
Overweight-(%) 30?030?5
Mean age at menarche (years) – 11?41?1
MET, metabolic equivalents.
*Average daily hours of viewing television, videos and video games combined.
-International Obesity Taskforce cut-off points for BMI for age and sex
(22)
.
Table 2 Daily hours of television, video and video game use by
sociodemographic characteristics of Mexican adolescents from
public schools in Morelos, Mexico (1999)
Males Females
Variable Mean SD Mean SD
Age (years)
11–12 5?92?95?63?0
13–14 5?73?15?33?0
15–16 6?02?94?72?9
17–18 6?62?76?13?0
Community type
Rural 5?33?15?13?0
Suburban 5?92?94?93?0
Urban 6?62?86?12?9
Socio-economic status
Low 6?22?95?13?1
Medium 5?33?15?23?0
High 6?62?75?82?9
Medical insurance
Uninsured 6?22?95?53
?0
Insured 5?73?05?33?0
Dieting
To lose weight 6?13?15?03?0
To gain weight 6?13?16?22?8
Not on a special diet 5?93?05?43?0
1940 M Lajous et al.
than those who said they wanted to gain weight. Mean
screen time increased significantly with the level of urba-
nicity and, in females, screen time increased with increasing
SES (P,0?01). Energy intake increased significantly with
increasing screen time in males and females (P,0?001).
The mean daily energy intake in males was 15 305 kJ for
,2 h of screen time/d and 18 759 kJ for .5 h/d. Females
had a mean daily energy intake of 15 166 kJ for ,2h of
screen time/d and 17 581 kJ for .5h/d.
In males, screen time was positively related to BMI
Z-score in age-adjusted and multivariate-adjusted ana-
lyses. In the multivariate-adjusted model, males with .5h
screen time/d had a 0?13 (95 % CI 0?04, 0?23) higher BMI
Z-score compared with males with ,2 h/d (Pfor trend
,0?003). In females, screen time was positively related
with BMI Z-score in age-adjusted analyses but not in
multivariate-adjusted analyses (Table 3).
Screen time was positively related to TSF and SSF in
males. After adjusting for confounding variables, males
with .5 h of screen time/d had a 1?08 mm (95 % CI 0?36,
1?81) greater TSF compared with males reporting ,2 h/d
(Pfor trend 50?01). Similarly, after adjusting for con-
founding variables, males with .5 h of screen time/d had
a0?73 mm (95 % CI 0?24, 1?22) greater SSF compared with
males with ,2 h/d (Pfor trend 50?006). In females,
screen time was positively related to TSF and SSF in age-
adjusted but not multivariate-adjusted analyses.
Age did not modify the association between screen time
and BMI Z-score or TSF in males or females. Nevertheless,
the association between screen time and SSF differed sig-
nificantly by age categories in males (Pinteraction 50?005).
A significant linear trend of increasing SSF with greater
screen time was found in younger but not older males
(Fig. 1). In females, age did not modify the association
between screen time and SSF. The association was however
modified by sexual maturity; screen time was positively
related to SSF among females who had not undergone
menarche (Pfor trend 50?04) but not among sexually
mature females (Pfor trend 50?75; Fig. 2).
Males spent 54 % of their screen time on videos and
video games, while females spent 48 %. For males, we
found a significant increasing trend only in BMI Z-score
when we analysed videos and video games indepen-
dently of television (P50?03). No association with tele-
vision by itself was found. In females, no associations
were observed when television and videos/video games
were analysed independently.
Discussion
The present study evaluated the association between time
spent viewing television, videos and video games and
measures of fat mass and distribution in a large survey of
Mexican adolescents in the State of Morelos. In males,
BMI Z-score, TSF and SSF were directly associated with
Table 3 Adjusted difference (and 95 % confidence interval) in BMI Z-score, triceps (TSF) and subscapular (SSF) skinfold thicknesses by television, video and video game use among Mexican
adolescents from public schools in Morelos, Mexico (1999)
BMI Z-score TSF SSF
Males Females Males Females Males Females
Television, video and
video games (h/d)
Age-
adjusted
Multivariate-
adjusted*
Age-
adjusted
Multivariate-
adjusted*
Age-
adjusted
Multivariate-
adjusted*
Age-
adjusted
Multivariate-
adjusted*
Age-
adjusted
Multivariate-
adjusted*
Age-
adjusted
Multivariate-
adjusted*-
,2 Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref.
2–2?9 Difference 0?09 0?04 20?01 20?02 0?98 0?72 20?09 20?34 0?46 0?38 0?22 0?08
95 % CI 20?08, 0?25 20?10, 0?17 20?08, 0?06 20?09, 0?05 20?07, 2?02 20?25, 1?70 20?61, 0?43 20?87, 0?20 20?26, 1?18 20?20, 0?95 20?17, 0?62 20?33, 0?48
3–3?9 Difference 0?16 0?03 0?04 0?02 1?11 0?47 0?68 0?28 0?84 0?26 0?54 0?29
95 % CI 0?03, 0?29 20?09, 0?15 20?03, 0?12 20?06, 0?10 0?31, 1?90 20?40, 1?34 20?05, 1?41 20?46, 1?02 0?21, 1?47 20?36, 0?88 0?05, 1?02 20?29, 0?77
4–4?9 Difference 0?22 0?05 0?08 0?04 1?67 0?93 0?94 0?28 1?20 0?39 0?72 0?33
95 % CI 0?10, 0?33 20?06, 0?15 20?01, 0?18 20?05, 0?14 0?64, 2?70 20?09, 1?95 0?17, 1?71 20?49, 1?06 0?53, 1?87 20?20, 0?98 0?08, 1?35 20?27, 0?94
$5 Difference 0?35 0?13 0?09 0?02 2?01 1?08 1?32 0?35 1?73 0?73 0?85 0?22
95 % CI 0?22, 0?48 0?04, 0?23 0?00, 0?17 20?07, 0?10 1?30, 2?72 0?36, 1?81 0?62, 2?03 20?29, 0?98 1?09, 2?36 0?24, 1?22 0?32, 1?38 20?22, 0?68
Pfor trend ,0?001 0?003 0?026 0?64 ,0?001 0?011 ,0?001 0?14 ,0?001 0?006 0?003 0?45
*Adjusted for age, height, socio-economic status, single-parent family, birth in hospital, parental education level, family income, family health insurance, physical activity, inactivity excluding television, video and video
games, community type, sexual maturity, diagnosis of asthma, dieting and frequency of restaurant dining.
-History of pregnancy and spontaneous abortion also included in females.
Screen time and adiposity in adolescents 1941
time spent viewing television, videos and video games.
The association of screen time with SSF seemed to be
stronger in 11- and 12-year-old males compared with
older youths. Conversely, no overall association of screen
time and anthropometric measures was observed among
Mexican female adolescents. An association between SSF
thickness and screen time was observed in sexually
immature females.
Our results are consistent with previous cross-sectional
and longitudinal findings on television viewing and
increased adiposity and obesity in Mexican and other
populations
(5–9,23–30)
. Nevertheless, others have reported
weak or no associations between television viewing and
physical inactivity and adiposity
(31–34)
. Disparate results may
be explained in part by differences in the age distribution of
participants, the cross-sectional nature of some studies and
the use of less comprehensive measures of media use.
Nevertheless, two randomized controlled trials of interven-
tions that reduced television and computer use lend strong
support to a causal relationship between screen time and
increased adiposity in younger children
(11,12)
. Moreover, a
recent analysis on the combined influence of not meeting
the current physical activity and screen time recommenda-
tions of 11 000–13 000 pedometer steps/d and ,2h/dfound
that overweight children were more likely to be non-com-
pliant with these recommendations
(35)
.
There are several indications that screen time plays a
different role within age and sex groups due to differences
–1·5
–1·0
–0·5
0·0
0·5
1·0
1·5
2·0
2·5
<2 2 3 4 5+
Total daily screen time (h)
Adjusted difference in SSF (mm)
Fig. 1 Adjusted difference in subscapular skinfold thickness (SSF, mm) with total daily screen time (h) by age group (—E—,
11–12 years; - - 3- -, 13–14 years; - - m- -, 15–16 years; - - &- -, 17–18 years) in Mexican male adolescents from public schools
in Morelos, Mexico (1999)
–0·2
0·3
0·8
1·3
1·8
2·3
<2 2345+
Total daily screen time (h)
Adjusted difference in SSF (mm)
Fig. 2 Adjusted difference in subscapular skinfold thickness (SSF, mm) with total daily screen time (h) by sexual maturity (—E—,
premenarcheal; —’—, postmenarcheal) in Mexican female adolescents from public schools in Morelos, Mexico (1999)
1942 M Lajous et al.
in the tempo of physical development. Most studies where
the link between screen time and increased adiposity or
obesity was found included children younger than 10 years
of age
(7–9,11,12,25,28–30)
. Studies that did not find the associa-
tion had a mean age closer to 13 years
(31–34)
. In the current
study, age did not appear to modify the association between
screen time and BMI and TSF. However, screen time was
directly associated with SSF among 11- and 12-year-old
males, who may not have undergone sexual maturation. In
line with previous reports
(31,32)
, we observed a null overall
association of screen time with adiposity in female adoles-
cents. However, we explored whether sexual maturity
modified the associations by stratifying on menarcheal
status and observed a significant increasing trend in SSF
thickness in sexually immature females (Pfor interac-
tion 50?053). SSF velocity and distance curves diverge
markedly in males and females during maturation. Results
of these post hoc analyses should be interpreted with
caution. Nevertheless, given null findings in studies with
older adolescents, the association of sedentary behaviour/
inactivity with measures of central fat distribution may be
partially explained by maturity and different maturational
tempos between males and females.
When we evaluated television and videos/video games
independently, we did not find an association with
anthropometric measures of adiposity and obesity.
Nevertheless, videos and video games represent close to
50 % of total screen time in this sample of Mexican ado-
lescents. The association with measures of fat mass and
distribution appeared to be driven by the combined
effects of these three activities, underscoring the impor-
tance of measuring the use of all electronic media.
Mechanisms thought to underlie the relationship between
screen time and adiposity are low energy expenditure due
to the substitution of physical activity by television viewing
and an increase in the consumption of energy-dense foods
advertised on television. Recent data lend stronger support
to energy intake as mediator of the effect of screen time
on adiposity
(36–38)
. A reduction in television viewing and
computer use was reported to significantly reduce daily
energy intake by close to 300 kcal (1255 kJ) over two
years, while no significant increase in physical activity
was observed over the same period
(11)
.
In the current study, we evaluated the association of
screen time and adiposity in a large sample of adolescents
using measures of both fat mass (BMI) and central (SSF)
and peripheral (TSF) fat distribution. We closely captured
recreational inactivity by using a questionnaire validated
in Mexican children
(9)
that estimates time spent on tele-
vision, video and video games on weekdays, Saturday
and Sunday. Height, weight, TSF and SSF thickness were
reliably measured with calibrated equipment by trained
personnel using standardized procedures. SSF, a measure
of central fat distribution, rarely has been available in
population-based studies of this magnitude and our
findings provide an interesting insight into its association
with screen time during maturation. Consistency in results
across different anthropometric measures with indepen-
dent measurement errors may further support the pre-
sence of the associations found in the present report.
Our study has some limitations that temper inter-
pretation of findings. First, causal inference is limited by
the cross-sectional design of the study. We hypothesized
that screen time was a determinant of increased adiposity,
but we were unable to assess whether a reverse effect
existed. Prior reports based on longitudinal data support
the directionality of the observed association. Second,
data on screen time and potential confounders are self-
reported, creating a potential for recall bias. However, we
believe that participants in this study population were
unaware that screen time could be a cause of increased
adiposity, so it is unlikely that obese or overweight ado-
lescents would have reported screen time differently from
their leaner counterparts. We are more concerned with
the potential for inaccurate reporting that would attenuate
of the associations. Third, our questionnaire did not
include computer use. At the time the survey was con-
ducted, the contribution of computer use to overall hours
spent in front of a screen was probably very limited in this
population. As in any observational study, our results
may be explained by the influence of unmeasured con-
founders. However, we were able to reduce this possi-
bility by adjusting for numerous socio-economic and
lifestyle variables.
We conclude that screen time is associated with
increased adiposity in Mexican adolescent males. The
association may be partly influenced by maturation;
screen time may be more important in younger adoles-
cents and be more influential in determining central fat
stores, as indicated by SSF. Our results underscore the
importance of understanding modifiable determinants of
adolescent obesity in the context of trends in Mexico. The
high prevalence of obesity and overweight in adolescents
may foreshadow an even greater surge in CVD and
diabetes in Mexico as these adolescents enter young
adulthood. Preventive interventions to promote physical
activity and limit screen time have been explored in
similar populations and were shown to be effective
(39)
.As
seen in other populations
(35)
, a thorough evaluation of
recommendations on physical activity and screen time in
the Mexican context would be important to support
public policy. Future research should focus on accurately
assessing screen time and physical activity and their
association with adiposity at the national level and on
identifying culturally tailored strategies to modify these
behaviours in Mexican youths.
Acknowledgements
M.L. was supported by the Mexican National Council for
Science and Technology (CONACyT), the Ministry of
Screen time and adiposity in adolescents 1943
Health of Mexico, the Cabot Family Charitable Trust and the
Epidemiology Department at the Harvard School of Public
Health (HSPH). J.C. was supported by the NIDDK training
grant T32-DK07703 and the HSPH Yerby Postdoctoral
Fellowship Program. The study was partly funded by
Bristol-Myers Squibb Foundation of New York, under the
initiative ‘Better Health for Women: A Global Health Pro-
gram’. Additional funding was provided by CONACyT grant
number 34487-M and the National Institute of Public Health
of Mexico (INSP). Elizabeth Devore participated in the initial
data management. None of the authors had a personal or
financial conflict of interest. Study design and data collec-
tion were performed by E.L.-P., M.H.-A., B.H.-P. and A.C.-V.
E.L.-P was responsible for funding the study. Analysis plan
and manuscript preparation were done by M.L., J.C., K.E.P.
and B.H.-P.
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