This study examined the relationship between demographic and socioeconomic factors and food consumption in Mexican adolescents. The study analyzed a representative sample of 7,218 Mexican adolescents aged 12-19. It found that only one-third consumed fruits and vegetables daily, less than half consumed dairy products daily, one-third drank soft drinks daily, and one-fifth consumed sweets and salty snacks. Adolescents from lower socioeconomic backgrounds and those who did not study or work were less likely to consume healthy foods like fruits, vegetables, and dairy products. The study concluded certain groups of adolescents in Mexico have less healthy diets and discussed socioeconomic and cultural factors that could explain the observed differences in food consumption.

1. Rev Panam Salud Publica/Pan Am J Public Health 24(2), 2008
127
Food consumption in Mexican adolescents
Luis Ortiz-Hernández and Blanca Lilia Gómez-Tello
Objective. To examine the relationship between demographic
and socioeconomic factors
and food consumption in Mexican adolescents.
Methods. A representative sample (n = 7 218) of Mexican
adolescents (12–19 years old)
was analyzed. Independent variables included age, gender, and
main activity of the adoles-
cents; gender and age of the head of household; socioeconomic
position; size of town (rural,
semiurban, or urban); and area of residence. The consumption
frequency of 13 food groups was
assessed. Through multivariate logistic regression models, the
effect of independent variables
over consumption frequency was evaluated.
Results. Among Mexican adolescents only one-third consumed
fruits and vegetables daily,
a little less than one-half consumed dairy products daily, one-
third drank soft drinks daily,
and one-fifth consumed sweets and salty snacks. Males reported
higher consumption of
legumes. Age increase was associated with higher frequency of
milk consumption. Adolescents
who worked and those who neither studied nor worked
consumed fruits, sweets, and salty
snacks less frequently. Eating fruits, vegetables, cereals, dairy

2. products, bread, starchy veg-
etables, red meat, white meat, and fast food decreased with
regard to socioeconomic position;
on the other hand, the lower socioeconomic strata had more
frequent consumption of legumes
and soft drinks.
Conclusions. There are groups of adolescents who are less
likely to consume healthy foods
(such as fruits, vegetables, and dairy products). Socioeconomic
and cultural processes that can
explain the differences observed are discussed.
Diet, adolescents, socioeconomic status, gender, Mexico.
ABSTRACT
Obesity in Mexico has been consid-
ered a public health problem, as it af-
fects a large number of people. In the
year 2000, among Mexican adolescents
aged 10–17 years, the prevalence of
overweight was 24.7% (1). For the year
2006 (2), the prevalence of overweight
and obesity in males 12–19 years of age
was 31.2%, while in females it was
32.5%. Similar to some other chronic
illnesses, obesity is related to eating
habits and consumption of energy and
macronutrients. In Mexico, during re-
cent decades, there has been an in-
crease in morbidity and mortality due
to diet-associated diseases, such as
obesity, high blood pressure, diabetes
mellitus, and coronary cardiopathy (3).

3. In 2005, 20.4% of Mexicans were be-
tween 12 and 19 years of age (4). Char-
acterizing eating habits in adolescents
is important because dietary habits ini-
tiated at these ages have a higher prob-
ability of persisting during adult life
(5). Additionally, obese adolescents
have a higher risk of morbidity in
adulthood due to coronary cardiopa-
thy, arteriosclerosis, and gout (6).
With the exception of reproductive
health-related topics, other aspects as-
sociated with the health and nutri-
tional conditions of adolescents have
been a matter of less interest. In con-
trast, the nutritional status and diet of
other age groups, such as preschool
Key words
Investigación original / Original research
Ortiz-Hernández L, Gómez-Tello BL. Food consumption in
Mexican adolescents. Rev Panam Salud Pu-
blica. 2008;24(2):127–35.
Suggested citation
Health Care Department, Metropolitan Autonomous
University–Xochimilco, Mexico City, Mexico. Send
correspondence to: Luis Ortiz-Hernández (UAM-X),
Calzada del Hueso 1100, Col. Villa Quietud,
Coyoacán, 04960 México, D.F., México; phone: (+52)
(55) 5483-7573; fax: (+52) (55) 5483-7218; e-mail:

4. [email protected]
and adult populations, have been
studied more. This situation probably
results from adolescents having low
mortality due to infectious and chronic
diseases (5).
Nutritional problems frequently ob-
served in adolescents from industrial-
ized countries comprise the following:
low consumption of fruits and vegeta-
bles; frequent consumption of foods
with high energy density; and defi-
ciencies of certain micronutrients such
as zinc, calcium, iron, and vitamin A
(5, 7). However, few studies have been
conducted (8–10) that describe the
food consumption of adolescents from
middle- and low-income countries.
In industrialized nations, persons of
lower socioeconomic position have
less healthy diets than individuals
with higher socioeconomic position
(11); nonetheless, there is evidence (10)
that these findings could not be ex-
trapolated to middle- or low-income
countries. Additionally, there are few
studies in adolescents on the role of
certain demographic characteristics in
food consumption, such as occupa-
tional activity or the size of the town
where they live. The aim of this re-

5. search was to examine the association
of socioeconomic and demographic
factors with food consumption in ado-
lescents from Mexico.
MATERIALS AND METHODS
The 2005 National Youth Survey
(NYS05) database was analyzed (12).
The sample design was probabilistic,
stratified, and multistage. For sam-
pling, Mexico was divided into five
geographic regions (described later).
In each region, census tracts were se-
lected in proportion to the number of
inhabitants. Sampling stages included
census tracts, blocks, households, and
subjects. In households, one subject
aged 12–29 years was selected; if there
were two or more eligible respon-
dents in the household, the subject
whose birth date was nearer in time
was chosen to interview. After data
were edited, the sample (n) included
7 218 cases that represented the entire
adolescent 12- to 19-year-old popula-
tion of Mexico. Using the sampling
weights, these data correspond to an
estimated total population (N) size of
16 384 551 adolescents. The nonre-
sponse rate was 15%, and the error
margin was 1.8%. Information was
gathered by means of a questionnaire
applied at face-to-face interviews. Par-
ticipant adolescents gave verbal con-

6. sent, and they were isolated from their
families to ensure confidentiality and
thus improve the quality of the data.
The following demographic char-
acteristics were analyzed: age of the
adolescents (12–14, 15–17, and 18–19
years), main activity of the adolescents
(only studying, only working, study-
ing and working, and neither studying
nor working), and gender and age of
the head of household (≤ 29, 30–39,
40–49, 50–59, and ≥ 59 years).
Socioeconomic position was evalu-
ated through two indicators: edu-
cation of the head of household (as
defined by the interviewee) and
household assets. Four categories
were used with respect to education:
very low (primary school or less), low
(secondary school or secretarial ca-
reer), middle (high school, technical
career, or teacher training), and high
(bachelor’s degree or more). Assets
found less frequently in Mexican
households were selected to estimate
an index based on household posses-
sions (4): washing machine, refrigera-
tor, telephone, car or van, computer,
and heater or gas boiler. The number
of assets in each household were
added, and four strata were formed:
very low (two or fewer assets); low
(three or four assets); medium (five as-
sets), and high (six assets).

7. Town size was divided into three
categories: rural (≤ 2 499 inhabitants),
semiurban (2 500–19 999 inhabitants),
and urban (≥ 20 000 inhabitants). The
32 Mexican states were divided into
five regions or area of residence:
Northwest, Northeast, Central-West,
Central, and South.
The frequency of intake of 13 food
groups was assessed: fruits, vegetables,
cereals (wheat and oats), starchy veg-
etables (potatoes and sweet potatoes),
legumes (beans, broad beans, and
lentils), dairy products, red meat (beef
and pork), white meat (chicken and
fish), soft drinks, sweets, salty snacks,
fast food (hot dogs, sandwiches, and
tortas), and bread. Response options
were the following: never, every now
and then, at sometime during the week,
and daily. All the response options
were dichotomized. For fruits, vegeta-
bles, cereals, dairy products, bread, soft
drinks, sweets, and salty snacks, the fol-
lowing groups were formed: (1) daily
consumption, and (2) consumption at
sometime during the week, every now
and then, and never. For starchy veg-
etables, legumes, red meat, white meat,
and fast food, the groups were (1) daily
consumption and at sometime during
the week, and (2) consumption every
now and then and never.

8. For statistical analysis, sample
weights considering sample post-
stratification were used, because they
allowed the sample’s gender and age
distribution to better approximate that
registered by the 2000 General Popula-
tion and Housing Census. Analysis
was done with SAS software, which al-
lows taking into account NYS05’s com-
plex design. Absolute and relative fre-
quencies of variables were obtained.
Later, multivariate logistic regression
models were estimated, in which the
dependent variables were food con-
sumption and the independent vari-
ables comprised age, gender, and main
activity of the adolescents; socioeco-
nomic position, age, and gender of the
head of household; size of town; and
area of residence. As a first step, all in-
dependent variables in each model
were included and were progressively
dismissed if their association with food
consumption was not statistically sig-
nificant (P > 0.050). From logistic re-
gression models, odds ratios (ORs)
were estimated with their correspond-
ing 95% confidence intervals (95% CI).
RESULTS
In Table 1, descriptive characteristics
of the population are shown. There
was nearly the same proportion of fe-
males and males; most adolescents

9. were between 12 and 14 years old, and
adolescents who only studied predom-
128 Rev Panam Salud Publica/Pan Am J Public Health 24(2),
2008
Original research Ortiz-Hernández and Gómez-Tello • Food
consumption in Mexican adolescents
inated. With both education and assets,
the low and very low socioeconomic
statuses predominated. For head of
household, 17.6% were females and
39.4% were 40–49 years of age.
Frequency of food consumption of
adolescents is presented in Table 2.
Foods such as dairy products, bread,
legumes, fruit, vegetables, and soft
drinks were consumed most fre-
quently, while foods consumed least
frequently were fast food, red meat,
and starchy vegetables.
Multivariate logistic regression-
model results are presented in Tables 3
to 5, with consumption of food groups
as the dependent variable. Fruit con-
sumption was higher in adolescents
living in households headed by older
persons but was lower in those who
both studied and worked; who neither
studied nor worked; who belonged to
the low and very low education status;

10. and who lived in Northeastern, North-
western, and Southern Mexico. Vege-
table consumption was lower in ado-
lescents who neither studied nor
worked, who had low socioeconomic
position (according to education or
household assets), and who lived in
the Northwest and South. Frequency
of cereal consumption was lower in
adolescents who worked, in those who
neither studied nor worked, in those
with low socioeconomic status (de-
fined by the two socioeconomic posi-
tion indicators), and in those who
lived in Northwestern Mexico. Dairy
products were less frequently con-
sumed by adolescents who worked;
those who neither studied nor worked;
those with low socioeconomic posi-
tion; those who lived in Northeastern,
Northwestern, and Southern Mexico;
and those who lived in households
headed by males.
Bread consumption was less fre-
quent in adolescents with low socio-
economic position and in those who
lived in Northeastern, Northwestern,
Central-Western, and Southern re-
gions. There was a higher frequency of
starchy vegetable consumption in in-
dividuals residing in semiurban locali-
ties; on the other hand, there was less
consumption of this food by individu-
als who worked, who had low socio-

11. economic status (defined by house-
hold assets), and who resided in
households in which the head was
older. Adolescents with low socioeco-
nomic position (defined by education
and household assets) and those who
resided in rural areas consumed less
red meat. White meat consumption
was lower in subjects living in rural
areas, in those who neither studied nor
worked, and in those with very low
socioeconomic status (defined by
household assets).
Soft drinks were less frequently con-
sumed by those residing in house-
holds headed by a male and in rural
areas; in contrast, soft drink intake was
higher in those with low socioeco-
nomic status. Adolescents with low so-
cioeconomic position consumed less
fast food, whereas those living in
Northeastern and Central-Western
Mexico consumed more of these foods.
Consumption of sweets was lower in
adolescents who worked and studied,
in those who neither studied nor
Rev Panam Salud Publica/Pan Am J Public Health 24(2), 2008
129
Ortiz-Hernández and Gómez-Tello • Food consumption in
Mexican adolescents Original research
TABLE 1. Sample descriptive characteris-
tics of Mexican adolescents, 2005

12. No. %
Sex
Male 3 471 49.2
Female 3 747 50.8
Age (years)
12–14 2 793 38.3
15–17 2 653 35.5
18–19 1 772 26.2
Main activity
Study 5 511 73.2
Work 543 9.8
Study and work 250 4.8
Neither study nor work 914 12.2
SEP,a education
Very low 3 002 45.4
Low 1 907 24.3
Medium 1 533 20.0
High 702 10.3
SEP, assets
Very low 2 079 33.2
Low 2 636 31.9
Medium 1 309 16.6
High 1 194 18.3
Sex of family’s head
Male 6 066 82.4
Female 1 152 17.6
Age of family’s head (years)
29 or less 297 5.8

13. 30–39 2 279 29.4
40–49 2 825 39.4
50–59 1 108 15.7
≥ 60 691 9.7
Size of town
Rural 547 0.5
Semiurban 1 669 12.5
Urban 5 002 87.0
Region
Central 1 178 31.0
Northeast 1 614 12.8
Northwest 384 7.4
Central-West 2 679 24.4
South 1 363 24.4
a SEP = socioeconomic position.
TABLE 2. Food consumption frequency of Mexican adolescents,
2005
Na ENTb SW c EDd
No. (%) (%) (%) (%)
Fruits 7 203 1.1 19.3 40.5 39.1
Vegetables 7 208 2.8 17.5 43.3 36.4
Cereals 7 200 7.8 25.8 39.6 26.8
Starchy vegetables 7 200 3.6 32.1 45.9 18.4
Dairy products 7 203 1.9 15.4 33.8 48.9
Legumes 7 204 0.8 19.8 38.4 41.0
Red meat 7 207 1.4 29.8 56.3 12.5
White meat 7 205 0.8 29.9 54.0 15.3
Soft drinks 7 205 4.1 28.3 34.5 33.1
Sweets 7 203 6.0 32.8 34.7 26.5

14. Salty snacks 7 205 7.1 35.6 33.5 23.8
Fast food 7 193 12.3 43.7 32.7 11.3
Bread 6 974 1.1 19.9 35.8 43.2
a N = never.
b ENT = every now and then.
c SW = sometime during the week.
d ED = every day.
worked, in those who lived in house-
holds headed by a male, and in ado-
lescents living in rural areas. Salty
snacks were less frequently consumed
by adolescents who worked, who nei-
ther studied nor worked, who lived in
households headed by a male, and
who lived in rural areas.
Consumption of legumes (n = 7 204,
N = 16 374 443) was higher in males
(OR = 1.66, 95% CI = 1.09–2.51, χ2 =
5.62, P = 0.018) and in individ-
uals with low socioeconomic status
as defined by education (χ2 = 15.30,
P = 0.002; middle socioeconomic sta-
tus: OR = 2.91, 95% CI = 1.58–5.34;
low status: OR = 2.40, 95% CI =
1.41–4.10; very low status: OR = 2.28,
95% CI = 1.27–4.10) (results not shown
in tables).
DISCUSSION

15. Considering dietary recommenda-
tions (13), the following findings are
worrisome: among Mexican adoles-
cents only one-third consumed fruits
and vegetables daily, a little less than
one-half consumed dairy products
daily, one-third drank soft drinks
daily, and one-fifth of Mexican adoles-
130 Rev Panam Salud Publica/Pan Am J Public Health 24(2),
2008
Original research Ortiz-Hernández and Gómez-Tello • Food
consumption in Mexican adolescents
TABLE 3. Regression models having as dependent variables
Mexican adolescents’ consumption of fruits, vegetables, cereals,
and dairy
products, 2005
Fruitsa Vegetablesa Cerealsa Dairy productsa
OR 95% CI OR 95% CI OR 95% CI OR 95% CI
n b 7 120 7 134 7 127 7 129
N b 16 189 000 16 216 049 16 207 862 16 206 347
Age (years) χ2 = 8.69, P = 0.013
12–14 NAc NA NA 1.00
15–17 1.26 0.89–1.78
18–19 1.81 1.22–2.67
Main activity χ2 = 14.92, P = 0.002 χ2 = 9.01, P = 0.029 χ2 =
17.22, P = 0.001 χ2 = 9.81, P = 0.020
Study 1.00 1.00 1.00 1.00
Work 1.16 0.62–2.19 0.73 0.44–1.22 0.45 0.24–0.85 0.58 0.35–

16. 0.95
Study and work 0.50 0.26–0.95 0.94 0.51–1.74 1.18 0.61–2.29
0.56 0.30–1.05
Neither study nor work 0.51 0.34–0.77 0.55 0.36–0.82 0.47
0.30–0.72 0.60 0.37–0.97
SEP,d education χ2 = 35.92, P = 0.000 χ2 = 8.98, P = 0.030 χ2 =
7.81, P = 0.050 χ2 = 10.13, P = 0.018
Very low 0.21 0.12–0.36 0.58 0.32–1.08 0.57 0.32–0.99 0.41
0.22–0.74
Low 0.27 0.16–0.46 0.43 0.23–0.78 0.54 0.30–0.95 0.39 0.21–
0.71
Medium 0.41 0.23–0.72 0.47 0.26–0.87 0.83 0.48–1.42 0.50
0.28–0.92
High 1.00 1.00 1.00 1.00
SEP, assets χ2 = 22.63, P = 0.000 χ2 = 33.66, P = 0.000 χ2 =
14.75, P = 0.002
Very low NA 0.32 0.19–0.54 0.26 0.16–0.42 0.38 0.23–0.64
Low 0.64 0.41–1.01 0.43 0.29–0.65 0.66 0.43–1.01
Medium 0.79 0.48–1.29 0.65 0.40–1.04 0.72 0.44–1.16
High 1.00 1.00 1.00
Sex of family’s head χ2 = 3.75, P = 0.053
Male NA NA NA 0.68 0.46–1.01
Female 1.00
Age of family’s head χ2 = 9.72, P = 0.045
29 or less 1.00 NA NA NA
30–39 1.64 0.70–3.84
40–49 2.13 0.91–4.97
50–59 2.36 1.01–5.61
60 or more 3.46 1.32–9.10
Region χ2 = 32.26, P = 0.000 χ2 = 16.71, P = 0.002 χ2 = 23.28,
P = 0.000 χ2 = 21.55, P = 0.000

17. Central 1.00 1.00 1.00 1.00
Northeast 0.54 0.34–0.85 0.70 0.44–1.10 0.76 0.49–1.20 0.50
0.33–0.76
Northwest 0.32 0.18–0.56 0.37 0.22–0.62 0.43 0.25–0.73 0.47
0.27–0.80
Central-West 1.12 0.78–1.61 0.85 0.59–1.22 1.32 0.97–1.81
0.84 0.62–1.13
South 0.53 0.32–0.88 0.58 0.35–0.97 0.67 0.41–1.10 0.45 0.28–
0.72
a The “every day” consumption frequency was modeled.
b The sample sizes are different because of differences in
amount of complete (or missing) data for different combinations
of variables.
c NA = not available because variables were not statistically
significant in regression models.
d SEP = socioeconomic position.
cents consumed sweets and salty
snacks. Low consumption of fruits and
vegetables has also been observed in
adolescents in Belgium (14), Costa
Rica (8), Spain (15–17), England (18,
19), and Scotland (20).
Although differences by gender
have been reported for consumption of
fruits, vegetables, dairy products, and
red meat (21), in Mexican adolescents
the only difference was found with re-
spect to legumes: males exhibited a
higher consumption. In Costa Rican
adolescents, the same trend was ob-

18. served (8), while in adolescents from
Scotland there were no differences (22).
NYS05 analysis showed that increased
age was associated with more frequent
consumption of dairy products. Food-
associated meanings could explain
these patterns: increased age and the
adoption of certain social roles (i.e.,
marriage) coincide with increased con-
sumption of foods that are symboli-
cally related to adulthood (i.e., dairy
products) (23).
In Mexico, adolescents who studied
and worked and those who neither
studied nor worked consumed fruits,
sweets, and salty snacks less fre-
Rev Panam Salud Publica/Pan Am J Public Health 24(2), 2008
131
Ortiz-Hernández and Gómez-Tello • Food consumption in
Mexican adolescents Original research
TABLE 4. Regression models having as dependent variables
Mexican adolescents’ consumption of bread, starchy vegetables,
red meat,
and white meat, 2005
Breada Starchy vegetablesb Red meatb White meatb
OR 95% CI OR 95% CI OR 95% CI OR 95% CI
n c 6 974 7 182 7 133 7 205
N c 15 406 961 16 337 921 16 207 060 16 371 606

19. Main activity χ2 = 13.47, P = 0.004 χ2 = 12.92, P = 0.005
Study NAd 1.00 NA 1.00
Work 0.37 0.21–0.66 0.60 0.32–1.12
Study and work 0.71 0.37–1.38 0.70 0.34–1.46
Neither study nor work 0.66 0.40–1.09 0.46 0.29–0.74
SEP,e education χ2 = 15.59, P = 0.001
Very low NA NA 0.34 0.20–0.59 NA
Low 0.39 0.22–0.69
Medium 0.45 0.24–0.84
High 1.00
SEP, assets χ2 = 10.73, P = 0.013 χ2 = 13.42, P = 0.004 χ2 =
8.88, P = 0.031 χ2 = 11.41, P = 0.010
Very low 0.53 0.33–0.85 0.57 0.35–0.93 0.47 0.26–0.86 0.40
0.23–0.70
Low 0.96 0.64–1.45 1.06 0.66–1.73 0.87 0.52–1.44 0.69 0.42–
1.13
Medium 0.68 0.42–1.10 1.25 0.72–2.16 0.77 0.43–1.39 0.59
0.34–1.04
High 1.00 1.00 1.00 1.00
Sex of family’s head χ2 = 3.65, P = 0.056
Male 0.71 0.50–1.01 NA NA NA
Female 1.00
Age of family’s head χ2 = 10.24, P = 0.034
29 or less NA 1.00 NA NA
30–39 0.36 0.15–0.88
40–49 0.42 0.17–1.03
50–59 0.58 0.24–1.44
60 or more 0.32 0.12–0.81
Size of town χ2 = 7.61, P = 0.022 χ2 = 10.26, P = 0.006 χ2 =
7.88, P = 0.020

20. Rural NA 1.11 0.65–1.91 0.45 0.27–0.76 0.47 0.27–0.81
Semiurban 1.78 1.18–2.68 1.01 0.65–1.56 0.98 0.63–1.52
Urban 1.00 1.00 1.00
Region χ2 = 42.70, P = 0.000
Central 1.00 NA NA NA
Northeast 0.41 0.26–0.64
Northwest 0.22 0.13–0.36
Central-West 0.55 0.39–0.77
South 0.55 0.35–0.87
a The “every day” consumption frequency was modeled.
b The “sometime during the week” and “every day”
consumption frequency were modeled.
c The sample sizes are different because of differences in
amount of complete (or missing) data for different combinations
of variables.
d NA = not available because variables were not statistically
significant in regression models.
e SEP = socioeconomic position.
quently; those who neither studied nor
worked consumed vegetables, cereals,
dairy products, and white meat less
frequently. Adolescents who worked
ate cereal, dairy products, and starchy
vegetables less frequently. Similar pat-
terns were observed in Irish adoles-
cents (22). These results could indicate
that entering the labor market is re-
lated to the adoption of unhealthy eat-
ing habits, which could result from
these adolescents having their own in-
come, which allows them to consume

21. meals prepared outside the home,
which tend to have fewer nutrients
and higher energy density (24, 25).
In Mexico, increased age of the head
of household was positively related to
adolescent fruit consumption as well
as to lower consumption of starchy
vegetables. It is possible that as heads
of household advance in age, they de-
velop more child-rearing skills and are
more concerned about healthy behav-
iors; thus, they tend to provide more
food in the home that is perceived to
be healthy. With regard to the latter,
among Australian adults (26), those
aged between 35 and 49 years con-
sumed more fruits, vegetables, and
fish but fewer cereals, dairy products,
meat, snacks, and sweets than the 18-
to 34-year age group.
Considering that women more com-
monly adopt health-associated behav-
iors (16, 18, 27, 28), we expected that
adolescents from households headed
by females would have higher con-
sumption of foods such as fruits, veg-
etables, and milk and lower consump-
tion of foods with high energy density.
The lower consumption of dairy prod-
132 Rev Panam Salud Publica/Pan Am J Public Health 24(2),
2008

22. Original research Ortiz-Hernández and Gómez-Tello • Food
consumption in Mexican adolescents
Table 5. Regression models having as dependent variables
Mexican adolescents’ consumption of soft drinks, fast food,
sweets, and salty
snacks, 2005
Soft drinksa Fast foodb Sweetsa Salty snacksa
OR 95% CI OR 95% CI OR 95% CI OR 95% CI
n c 7 205 7 119 7 203 7 205
N c 16 378 624 16 189 514 16 373 658 16 377 539
Main activity χ2 = 16.12, P = 0.001 χ2 = 12.23, P = 0.007
Study NAd NA 1.00 1.00
Work 0.54 0.28–1.02 0.50 0.26–1.00
Study and work 0.44 0.22–0.85 0.40 0.19–0.84
Neither study nor work 0.50 0.32–0.78 0.61 0.39–0.96
SEP,e education χ2 = 13.03, P = 0.005
Very low NA 0.65 0.36–1.16 NA NA
Low 0.67 0.38–1.21
Medium 1.43 0.77–2.65
High 1.00
SEP, assets χ2 = 7.86, P = 0.050 χ2 = 20.40, P = 0.000
Very low 0.85 0.54–1.33 0.34 0.21–0.54 NA NA
Low 1.43 0.98–2.09 0.59 0.39–0.88
Medium 1.20 0.76–1.91 0.56 0.37–0.90
High 1.00 1.00
Sex of family’s head χ2 = 10.21, P = 0.001 χ2 = 5.29, P = 0.022
χ2 = 4.21, P = 0.040

23. Male 0.53 0.36–0.78 NA 0.59 0.38–0.93 0.62 0.39–0.98
Female 1.00 1.00 1.00
Size of town χ2 = 21.47, p = 0.000 χ2 = 16.27, P = 0.000 χ2 =
14.40, P = 0.001
Rural 0.31 0.18–0.52 NA 0.35 0.21–0.58 0.31 0.17–0.57
Semiurban 0.62 0.42–0.91 0.88 0.58–1.35 1.00 0.65–1.51
Urban 1.00 1.00 1.00
Region χ2 = 12.54, P = 0.014
Central NA 1.00 NA NA
Northeast 2.01 1.32–3.06
Northwest 1.27 0.80–2.03
Central-West 1.44 1.07–1.92
South 1.17 0.75–1.84
a The “every day” consumption frequency was modeled.
b The “sometime during the week” and “every day”
consumption frequencies were modeled.
c The sample sizes are different because of differences in
amount of complete (or missing) data for different combinations
of variables.
d NA, not available because variables were not statistically
significant in regression models.
e SEP = socioeconomic position.
ucts observed in Mexican adolescents
living in households headed by males
supports this idea; nonetheless, these
adolescents also consumed bread, soft
drinks, sweets, and salty snacks less
frequently. A possible reason for this
finding is that, in households headed
by males, it is more likely that a

24. woman (i.e., the wife) plans, pur-
chases, and prepares family meals. On
the other hand, when a female is the
head of household, she is usually a sin-
gle mother holding a salaried job,
which limits her time for planning,
buying, and preparing meals. Thus, fe-
male heads of household tend to pur-
chase convenient and industrially
processed food items.
In Mexican adolescents, consump-
tion of fruits, vegetables, cereals, dairy
products, starchy vegetables, bread,
red meat, white meat, and fast food di-
minished with decreasing socioeco-
nomic position; conversely, individuals
in a low social position consumed
legumes and soft drinks more fre-
quently. In industrialized countries,
adolescents with low social status had
lower consumption of fruits (29, 30),
vegetables (15, 31–34), cheese (34, 35),
and milk (30, 34). It has been observed
that Australian adults with low socio-
economic position consumed more
legumes (26). In adolescents in North-
ern, Southern, and Western European
countries (15, 29), soft-drink consump-
tion was negatively related to socio-
economic position; the opposite was
observed in Central and Eastern Euro-
pean countries (29). There is no consis-
tent pattern for the remaining foods. In
Spanish adolescents, consumption of
salty snacks was negatively related to

25. socioeconomic position (15), whereas
in Swedish adolescents it was not re-
lated to fast food consumption (34);
however, in Swedish female adoles-
cents—but not in males—a socioeco-
nomic index of residence areas was
negatively related to meat, fish, and
egg intake (34). In Finnish children and
adolescents, there were no socioeco-
nomic differences in consumption of
meat and meat products (30). In adoles-
cents from two Chinese provinces, con-
sumption of fruits, juices, milk, yogurt,
and soft drinks was lower in the low
socioeconomic group, although rice in-
take was higher; in addition, males
with high socioeconomic position had
higher consumption of shrimp, pork,
hamburgers, and chocolate (10). In
Costa Rican adolescents, the parents’
educational level was positively related
to fruit and vegetable intake (9).
Socioeconomic differences regarding
food consumption observed among
Mexican adolescents could be partially
attributed to food prices in the coun-
try: the least expensive products com-
prise sugar, oils, and cereals, followed
by meat and canned fish, dairy prod-
ucts, vegetables, and fruits; the most
expensive product is fresh seafood
(36). Although in Mexico the prices of
beef and chicken, industrialized food
(which includes snacks), and food

26. prepared outside the home have de-
creased over the past years, these
products remain more expensive than
others such as sugar and legumes.
Moreover, during the past decade the
price of basic cereals, such as corn, has
increased (36).
With NYS05 data, it was observed
that the two indicators for socioeco-
nomic position were independently
associated with consumption of cer-
tain foods. In multivariate models, the
head of household’s education and the
indicator based on household assets
were positively associated with con-
sumption of vegetables, cereals, dairy
products, red meat, and fast food. This
result supports the notion that each so-
cioeconomic position indicator mea-
sures a different dimension of social
stratification (37); therefore, they can
be independently related to health be-
haviors. Education is the cultural di-
mension indicator of socioeconomic
stratification, while the household as-
sets indicator reflects the wealth of the
household. The head of household’s
education was negatively related to
consumption of legumes; additionally,
soft drink consumption was higher in
the low and medium strata, as defined
by the household-assets indicator, but
it was lower in the high and very low
socioeconomic strata. This pattern can-
not be explained by food prices, be-

27. cause legumes are inexpensive and
therefore are accessible to individuals
in the higher strata, while soft drinks
in Mexico remain more expensive than
other food types (36). Bourdieu (27)
stated that starchy foods (such as cere-
als and legumes) and those with high
energy density are preferred by per-
sons with low socioeconomic position
because these foods have been sym-
bolically associated with qualities such
as physical strength.
Compared with Mexican adoles-
cents residing in urban localities, those
living in rural areas consumed red
meat, white meat, soft drinks, sweets,
and salty snacks less frequently; ado-
lescents from semiurban localities con-
sumed starchy vegetables more fre-
quently but fewer soft drinks. These
differences can be attributed to the fact
that urbanization leads to a greater
availability of food, especially indus-
trially processed food products. In
Chinese male adolescents, those resid-
ing in urban areas exhibited a higher
intake of fruits, juice, milk, and yogurt;
in Chinese female adolescents, differ-
ences were also observed in fruit and
milk consumption, but the opposite
pattern was observed for rice con-
sumption in both genders and for veg-
etables in males (10). In Costa Rican
adolescents, those living in urban

28. areas had a higher intake of vegetables
but a lower intake of fruits (8). In high-
income countries, no clear patterns
have been observed with respect to
food consumption when comparing
urban and rural localities (15, 34).
Compared with adolescents in Cen-
tral Mexico, those residing in North-
eastern and Central-Western Mexico
consumed fast food more frequently.
These regions are characterized as
having greater economic development
and more livestock; additionally, be-
cause of their geographic proximity to
the United States, it may be implied
that these are the first regions where
fast food restaurants appeared. On the
other hand, adolescents in Central
Mexico tended to consume more
fruits, vegetables, dairy products, cere-
als, and bread. Mexico City is included
in this region, where one-fifth of the
Mexican population lives and where
the country’s most important food dis-
tribution centers are located.
Rev Panam Salud Publica/Pan Am J Public Health 24(2), 2008
133
Ortiz-Hernández and Gómez-Tello • Food consumption in
Mexican adolescents Original research
In Mexico, one-third of adolescents

29. are overweight or obese (2); the regions
with the highest rates are the North
(29.4% in males and 31.1% in females)
and Mexico City (28.5% and 31.6%, re-
spectively); in contrast, the South
(20.0% and 24.9%, respectively) has the
lowest prevalence of overweight and
obesity. Our findings show that the fre-
quency and distribution of consump-
tion of food with high energy density
are similar to the rates of overweight
and obesity; the proportion of adoles-
cents who daily ingested soft drinks,
sweets, and salty snacks are 33.1%,
26.5%, and 23.8%, respectively. Coinci-
dentally, the North region is where
more adolescents eat fast food. This sit-
uation must translate in the design and
execution of nutrition education pro-
grams focused on reducing the intake
of food with high energy density, espe-
cially in the North and Mexico City.
One limitation of this research
comprises the dietary assessment in-
strument. This is due to the following:
(1) The investigated food groups in the
questionnaire were general; thus, a
more detailed analysis concerning spe-
cific foods was not possible. (2) It
would be helpful to evaluate sepa-
rately certain food items included in
the same groups (i.e., fish and chicken),
because their consumption might not
be related. (3) The consumption of

30. some important foods in the Mexican
diet was not assessed, such as eggs,
tortillas, and Mexican dishes. (4) Cer-
tain consumption-frequency options
are ambiguous (i.e., “every now and
then,” and “sometime during the
week”) and do not permit evaluating
the number of servings consumed. Al-
though the questionnaire did not allow
us to know food consumption in
grams, it did allow us to identify dif-
ferences in consumption levels. In ad-
dition, a strength of the investigation
lies in that a probabilistic sample was
interviewed, which makes it possible
to obtain a general view of dietary
habits in Mexican adolescents.
The analysis allowed us to identify
groups of adolescents with problem-
atic food consumption: the young-
est adolescents consumed milk less
frequently; those who studied and
worked and those who neither studied
nor worked consumed fruits less fre-
quently, and the group living in house-
holds headed by younger persons con-
sumed less fruit. In addition, those
residing in households headed by fe-
males consumed more bread, soft
drinks, sweets, and salty snacks; ado-
lescents with low socioeconomic posi-
tion consumed fruits, vegetables, and
dairy products less frequently but
drank soft drinks more frequently;

31. groups considered in a high socioeco-
nomic position consumed more fast
food but consumed legumes less fre-
quently; subjects living in urban areas
consumed more soft drinks, sweets,
and salty snacks, and those residing in
Northeastern and Central-Western
Mexico consumed more fast food.
Some of the observed results in the
Mexican sample are similar to those re-
ported by others, which confers higher
validity to the conclusions obtained
here. This knowledge can be used to
design nutritional education pro-
grams. Nevertheless, it should be
considered that certain differences in
consumption can be the result of so-
cioeconomic or cultural processes,
which are difficult to modify. Finally,
some of the proposed explanations for
understanding the observed differ-
ences in food consumption require ver-
ification through qualitative research.
Acknowledgments. We are grateful
to the Mexican Institute of Youth for
allowing access to the Youth National
Survey (YNS) 2005 database. This
work could not have been conducted
without technical information on the
YNS graciously provided by Lic. Sofia
Serrano-F. (Instituto Mexicano de la
Juventud).
134 Rev Panam Salud Publica/Pan Am J Public Health 24(2),
2008

32. Original research Ortiz-Hernández and Gómez-Tello • Food
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consumir alimentos
saludables (como frutas, vegetales y productos lácteos). Se
discuten las condiciones
socioeconómicas y culturales que pueden explicar las
diferencias observadas.
Dieta, adolescente, nivel socioeconómico, México.
RESUMEN
Consumo de alimentos
en adolescentes mexicanos
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Manuscript received on 16 October 2007. Revised version
accepted for publication on 19 May 2008.
R E S E A R C H P A P E R
Childhood Obesity and Unhappiness: The Influence
of Soft Drinks and Fast Food Consumption
Hung-Hao Chang Æ Rodolfo M. Nayga Jr.
Published online: 21 March 2009
� Springer Science+Business Media B.V. 2009
Abstract A growing body of literature has examined the
determinants of childhood
obesity, but little is known about children’s subjective
wellbeing. To fulfill this gap, this
paper examines the effects of fast food and soft drink
consumption on children’s over-

40. weight and unhappiness. Using a nationwide survey data in
Taiwan and estimating a
simultaneous mixed equation system, our results generally
suggest a tradeoff in policy
implication. Fast food and soft drink consumption tend to be
positively associated with
children’s increased risk of being overweight but they are also
negatively associated with
their degree of unhappiness. Current and future policy/program
interventions that aim to
decrease fast food and soft drinks consumption of children to
reduce childhood obesity
may be more effective if these interventions also focus on ways
that could compensate the
increase in degree of unhappiness among children.
Keywords Unhappiness � Childhood obesity � Fast food � Soft
drink � Taiwan
1 Introduction
The World Health Organization (WHO) has reported that
obesity has become a growing
threat to human health both in developing and developed
countries (World Health Orga-
nization 2000). The prevalence of childhood obesity is also of

41. increasing public concern
around the world. For example, in Taiwan, childhood obesity
has increased dramatically
over the past decades. In 1970, only about 2% of Taiwanese
school-children were con-
sidered obese. By 1988, this figure has risen to 17% (Wu 2001).
To date, one in every four
H.-H. Chang (&)
Department of Agricultural Economics, National Taiwan
University, No 1, Roosevelt Rd Sec 4,
Taipei 10617, Taiwan
e-mail: [email protected]
R. M. Nayga Jr.
Department of Agricultural Economics and Agribusiness,
University of Arkansas, Fayetteville,
AR 72701, USA
e-mail: [email protected]
123
J Happiness Stud (2010) 11:261–275
DOI 10.1007/s10902-009-9139-4
children is now considered overweight in Taiwan (Taiwan
Medical Association for the
study of obesity (TMASO) 2007).
Childhood obesity is a major public health problem that has
both individual and

42. environmental causes. Among all of the factors that may be
related to children’s body
weight, the promotion of healthy eating has become a target of
health promotion and
research programs (Ludwig et al. 2001). Consequently, a
number of nutrition and public
health studies suggest the importance of examining the
influence of fast food consumption
on children’s weight (e.g., Bowman et al. 2004; Hsieh and
FitzGerald 2005; Hui et al.
2003). In addition to fast food consumption, the association
between children’s soft drinks
(i.e., sugar-sweetened beverages) consumption and obesity has
also been discussed in the
literature (e.g., Andersen et al. 2005; Ariza et al. 2004; Berkey
et al. 2004; Forshee et al.
2004; Troiano et al. 2000). Some studies suggest that
consumption of sugar-sweetened
beverages leads to higher energy intakes, which may place
children at risk for excess
weight gain and obesity (Andersen et al. 2005; Anderson et al.
2003; Troiano et al. 2000).
However, empirical evidence found in the previous studies is
still inconclusive. For

43. instance, based on data consisting of 10,371 children drawn
from the U.S. National Health
and Nutrition Survey, Troiano et al. (2000) found that soft
drinks contributed to high
proportions of energy intakes among overweight children. In
contrast, the results presented
by Andersen et al. (2005) using data from 3,139 children in
Norway showed an insig-
nificant association between consumption of soft drinks and
overweight.
Little is known as well about the relationship between fast food
and soft drinks con-
sumption as well as the extent to which these consumption
behaviors may affect children’s
subjective wellbeing or happiness. Addressing the association
between children’s sub-
jective wellbeing and food consumption is of particular policy
interest because the
prevalence of children’s mental health problems has been
increasing dramatically in recent
years (e.g., Currie and Stabile 2006; Lindberg and Swanberg
2006). In Taiwan, approxi-
mately 38% of school children have psychological or behavioral
problems (Lin 2002).

44. Understanding the effects of factors that are correlated with
children’s body weight and
their psychological/mental health is crucial in that if the
reduction in children’s body
weight improves their physical health, the decrease in the
likelihood of subjective well-
being may result in an adverse effect on their psychological or
mental health. Hence,
policies and programs that aim to improve children’s overall
health should take these
effects on children objective (i.e., obesity) and subjective (i.e.,
unhappiness) wellbeing into
account.
Research focusing on individual’s subjective wellbeing has
received great attention
recently due to the fact that the rational vision of economic
decision-making has come
under increasing scrutiny (Graham 2005). Since the maximum
utility framework cannot
explain many circumstances of individual’s decisions, an
alternative indicator of human
wellbeing from the field of psychological science has been
proposed to explain human
behavior (e.g., Anand and Clark 2006; Cummins 2000).

45. 1
One of the common indicators is
‘‘happiness’’ or ‘‘unhappiness’’, which measures individual’s
subjective wellbeing.
Recently, the use of happiness indicator has received increasing
attention from economists
(e.g., Frey and Stutzer 2002; Graham 2005; Easterlin 2001;
Kahneman and Krueger 2006).
Most of the studies related to subjective wellbeing are focused
on the examination of the
factors associated with adult’s subjective wellbeing. However,
not much attention has been
paid on children.
1
Several indicators from the psychological science can also be
found in Frey and Stutzer (2002).
262 H.-H. Chang, R. M. Nayga Jr.
123
The focus of this paper is based on two important questions.
First, what factors are
associated with children’s fast food and soft drink
consumption? Second, how do these two

46. types of consumption influence children obesity and
unhappiness? Using a nationwide
survey data in Taiwan, our empirical results suggest that
children’s fast food and soft drink
consumption are influenced by children’s characteristics and
household features. Addi-
tionally, both soft drinks consumption and fast food
consumption are positively associated
with children’s overweight and negatively associated with
degree of unhappiness. If the
likelihood of children’s overweight and happiness represent
their objective and subjective
wellbeing, our finding suggests that consumption of fast food
and soft drinks can result in a
tradeoff between children’s objective and subjective wellbeing.
The remainder of this paper is constructed as follows. The data
used in this study is
introduced in the following section. We then discuss the
econometric strategy. After then
presenting and discussing the empirical results, we conclude
with a brief summary and a
discussion of policy implications.
2 Data

47. We conduct the empirical analysis using data drawn from the
National Health Interview
Survey at Taiwan (NHIS) in 2001. NHIS is an enumerative
national survey conducted by
the National Health Research Institute of Taiwan (NHRI) to
gather information on health
status and health behavior of the citizens. NHIS data were
collected using a standardized
face-to-face interview between August 2001 and January 2002,
and a multistage stratified
sampling scheme was used to select a probability sample. In the
first stage, 359 townships
of Taiwan were divided into seven regions according to their
geographic location. The
townships in each region were chosen based on their population
size. Within each town-
ship, a number of lins (i.e., a smaller unit than township) were
sampled with their
population size.
2
Therefore, NHIS is representative of the non-institutionalized
population
in Taiwan (Lo et al. 2003). In all, 6,592 households and 26,658
adults were interviewed. In

48. addition, it captured survey data on a total of 3,977 children
under 12 years old. These
adults and children data sets can be linked to each other based
on the identification number
of each household. Since the cutoff points for body weight are
only applicable for children
above 2-years old, we first limit our analysis to a sub-sample of
children between 2 and 12-
years old. To capture the characteristics of the parents, we
linked the adult data to the child
data set.
3
We then deleted the missing values of some key variables (such
as body weight)
in the data, resulting in 2,366 children.
4
With respect to fast food and soft drinks consumption,
respondents of NHIS are asked
the following questions: ‘‘How often does your child consume
the following food item?’’
There are five categories that each respondent’s answer may fall
into: never, seldom,
sometimes, often, and always. We assign a value between 0–4
(i.e., 0 for never, 1 for

49. seldom, 2 for sometimes, 3 for often, and 4 for always) to the
answers for each food item
and sum up the scores for food items: French fries, pizza, and
hamburger. This sum
represents our measurement for fast food consumption (the
variable FASTFOOD). Also,
2
Detailed descriptions of the survey designs can be found in Lo
et al. (2003) and Pan et al. (2003).
3
We exclude the children sample if their parents didn’t live with
them.
4
To avoid the clustering effects as a result of multiple children
from the same family, we follow the method
used in McIntosh et al. (2006) to randomly select only one child
from each household.
Childhood Obesity and Unhappiness 263
123
the corresponding scores for soda and other sugar-sweetened
beverages are our mea-
surement for soft drinks (the variable DRINK). In our sample,
the mean values are 2.86 and

50. 3.55 for children’s fast food and soft drink consumption,
respectively.
The other two variables of particular interests are children’s
weight status and the
degree of happiness. The weight status is defined by their body
mass index (BMI).
5
Unlike
the case of adults, children’s BMI cannot be directly used to
define their weight status, and
it has to be defined by age and gender based on the distribution
of the population in the
same age. For instance, a child above 2-years old with a BMI
above the 85th percentile and
less than the 95th percentile of the population is classified as at
risk of being overweight.
The same child with a BMI above 95th percentile is considered
at risk of being obese. In
this study, the cutoff points are made by age and gender and are
determined by the Taiwan
Health Department.
6
In our sample, approximately 25% of children are considered
over-

51. weight or obese. With respect to children’s degree of
unhappiness, respondents of NHIST
are asked the following questions: ‘‘How often does your child
feel unhappy, sad or
depressed?’’ Each respondent’s answer may fall into one of
three categories: never,
sometimes, and often. Due to the low percentage of responses in
the third category, we
combined the last two categories into a single category to
represent if the child ever feels
unhappy, sad, or depressed.
7
In so doing, a binary indicator UNHAPPY is used to indicate
if the child feels unhappy. The sample statistics show that about
19% of children some-
times or often feel unhappy, sad or depressed. With respect to
the influence of the fast food
and soft drinks consumption on children’s body weight and
unhappiness, it appears that
children with fast food and soft drink consumption are likely to
be overweight and less
unhappy (Table 1).
The other variables included in our analysis are built on the

52. empirical specifications
from some of the previous studies (e.g., Anderson et al. 2003;
Berkey et al. 2004; Bowman
et al. 2004; Crespo et al. 2001; Lin et al. 2004). Several
variables of children’s charac-
teristics, household features, and geographical conditions are
hypothesized to be associated
with children’s consumption, body weight, and happiness. In
addition to these factors,
mother’s consumption of fast food and soft drink are included
(FASTFOOD_M and
DRINK_M) to capture the importance of mothers’ consumption
behavior on children.
Children’s characteristics are represented by age and gender
(AGE and MALE). Because
soft drinks consumption has been shown to be associated with
dental care (e.g., Marshall
et al. 2003), a dummy variable that specifies if the child has a
routine visit with the dentist
(DENTIST) is included. Also, a dummy variable that specifies
if the child has ever stayed
Table 1 Sample means of overweight and unhappiness
Children with fast food or soft drink consumption

53. If child is overweight 0.26
If child is unhappy 0.17
Children without fast food or soft drink consumption
If child is overweight 0.22
If child is unhappy 0.22
5
It is measured as the ratio of weight (in kilogram) to height
squared (in meters).
6
The cutoff points for determining overweight or obese weight
status in Taiwan can be found on the
website
http://www.vghtpe.gov.tw/*nutr/forum/forum02/bmi2.htm.
7
The percentages of these categories in our sample are 80, 18,
and 2, respectively.
264 H.-H. Chang, R. M. Nayga Jr.
123
http://www.vghtpe.gov.tw/~nutr/forum/forum02/bmi2.htm
at the hospital in the past 6 months (HOSPITAL) is included to
reflect his/her health
condition. Several household characteristics are included as

54. well. Family incomes are
defined in several categories (HHINC2, HHINC3, HHINC4, and
HHINC5). To reflect the
effects of other household members on children’s behavior, the
variable LONGCARE
indicates if any of the household members needs long term
medical care. Finally, com-
pared to the northern area (the reference group), three regional
dummies (SOUTH, EAST,
CENTER) are specified to indicate if the household is located in
the south, east, and center
of Taiwan, respectively. Urbanization variables are also
specified to indicate if the
household is located in the central city (CITY) or county
(COUNTY). The sample statistics
of variables used in this study is listed in Table 2.
3 Econometrics Strategy
The econometric framework consists of two parts. First, we
estimate a mixed structure
simultaneous-equation system for the effects of factors that are
associated with children’s
fast food and soft drink consumption, and the likelihood of
being overweight, and

55. Table 2 Sample statistics
Variable definition Mean SD
Dependent variables
FASTFOOD Child’s fast food consumption (0–12) 2.86 1.88
DRINK Child’s sugar drink (0–8) 3.55 1.95
OVERWEIGHT If the child is overweight or obese (=1) 0.25
0.43
UNHAPPY If the child is unhappy (=1) 0.19 0.40
Mother’s food consumption
FASTFOOD_M Mother’s fast food consumption (0–12) 1.52
1.73
DRINK_M Mother’s sugar drink consumption (0–8) 3.14 1.81
Children characteristics
AGE Age of the child in years 7.14 2.87
MALE If male (=1) 0.51 0.50
HOSPITAL If ever stay in hospital in the previous year (=1)
0.06 0.23
DENTIST If dentist visit in the past 6 months (=1) 0.56 0.50
Household factors
HHINC2 If monthly income NT$50,000 * 70,000 (=1) 0.24 0.43

56. HHINC3 If monthly income is NT$70,000 * 100,000 (=1) 0.17
0.38
HHINC4 If monthly income is NT$100,000 * 150,000 (=1) 0.11
0.32
HHINC5 If monthly income is more than NT$150,000 (=1) 0.07
0.25
LONGCARE If any family member needs long care (=1) 0.12
0.33
Region and local economy conditions
CITY If located in central city (=1) 0.56 0.50
COUNTY If located in county area (=1) 0.23 0.42
CENTER If located in central Taiwan (=1) 0.39 0.49
SOUTH If located in southern Taiwan (=1) 0.25 0.43
EAST If located in eastern Taiwan (=1) 0.04 0.20
2,366 children are included
Childhood Obesity and Unhappiness 265
123
unhappiness. To capture the potential correlations between
these behaviors, this model is

57. estimated with a simulated maximum likelihood estimation
method. To validate our
empirical specification, the second part of this section
introduces the statistical tests for
testing the endogeneity assumption and the restricted
exclusions.
3.1 Estimating the Mixed Structure Model
We estimate a four-equation simultaneous-equation system. The
first two equations rep-
resent the fast food and soft drink consumption of children, and
the other two equations
represent children’s likelihood of being overweight and
unhappiness. This model is mixed
in that children’s consumption of fast food and soft drink are
censored and the variables
representing children’s risk of being overweight and
unhappiness are binary indicators.
Suppose i represents each child, the simultaneous equation
system is specified as:
y�1i ¼ xib1i þ zik1 þ e1i
y�2i ¼ xib2i þ zik2 þ e2i
y�3i ¼ xib3i þ y1ia1 þ y2ia2 þ e3i
y�4i ¼ xib4i þ y1ic1 þ y2ic2 þ e4i
ð1Þ

58. yj ¼ y�j iff y
�
j [ 0 and yj ¼ 0 iff y
�
j 50 ðj ¼ 1 and 2Þ
yk ¼ 1 iff y�k [ 0 and yk ¼ 0 iff y
�
k 50 ðk ¼ 3 and 4Þ
where y1
*
and y2
*
are the unobserved latent variables that represent children’s fast
food
and soft drink consumption, respectively. y3
*
and y4
*
are the unobserved latent variables
that represent the likelihoods of being overweight and unhappy.
Since not every child
consumes fast food or soft drink, these two variables may be
censored at zero value. y3
and y4 are the binary indicators counterparts for the latent
variables y3

59. *
and y4
*
. Xi are
vectors of common exogenous factors that are associated with
child’s food consumption
and the risk of being overweight and unhappy. The vector Zi
contains the excluded
variables that are associated with child’s food consumption but
not directly affecting
his/her likelihood of being overweight and unhappy. The
vectors (a; b; c; k) are the
parameter of interests.
The vectors ej are random errors, which assume to follow a
multivariate normal dis-
tribution u ð0; RÞ, with zero mean and the covariance R
r21 ::: ::: :::
q21 r
2
2 ::: :::
q31 q32 1 :::
q41 q42 q43 1
2
664

60. 3
775.
For identification purpose, the variances of e3; e4 are
normalized to be 1 as the con-
ventional strategy used in the binary probit model (Greene
2003). Overall, 16 regimes can
be realized by the data, and the probability of each regime can
be derived. For instance, the
probabilities that (y1 [ 0, y2 [ 0, y3 = 1, y4 = 1) and (y1 = 0, y2
= 0, y3 = 0, y4 = 0)
are
8
:
8
To save space, we didn’t present the derivatives of the
probability of other regimes. However, they can be
derived in a similar way.
266 H.-H. Chang, R. M. Nayga Jr.
123
Pr ðy1 [ 0; y2 [ 0; y3 ¼ 1; y4 ¼ 1Þ
¼ fðe1; e2Þ
Z1
�Xb3�y1 a1�y2 a2

61. Z1
�Xb4�y1c1�y2 c2
gðe1; e2je3; e4Þ de1de2
ð2Þ
Pr ðy1 ¼ 0; y2 ¼ 0; y3 ¼ 0; y4 ¼ 0Þ¼
Z�Xb1
�1
Z�Xb2
�1
Z�Xb3
�1
Z�Xb4
�1
gðe1; e2e3; e4Þ de1de2de3de4:
ð3Þ
By combining the probability of the 16 possible regimes, the
consistent estimates can be
obtained by implementing the maximum likelihood estimation
method on the following
log-likelihood function.

62. log L ¼
XN
i¼1
log Prðy1; y2; y3; y4Þ � di ð4Þ
where the dummy indicator di represents the specific regime
that each individual may fall
into.
To estimate Eq. 4, it is necessary to evaluate the multivariate
normal density function.
The simulated maximum likelihood (SML) method based on the
Geweke-Hajivassiliour-
Keane (GHK) smooth recursive conditioning simulator is used.
It has been shown that the
GHK simulator is unbiased for any number of replications and
generates smaller variances
than other simulators (Train 2003). Additionally, it has been
shown to be the most
unambiguously reliable method for simulating normal
probabilities (Hajivassiliou et al.
1996). Simulating the multivariate normal probability in the
likelihood function is a
practical alternative to numerical evaluation of the probability
integrals.
Given the consistent estimates of the Eq. 4, the effects of the
fast food and the soft drink

63. consumption on children’s overweight and unhappiness can be
evaluated according to the
average treatment effects on the sample means (Greene 2003).
For instance, the effects of
fast food consumption on children’s overweight and
unhappiness can be shown as:
ATEðy3Þ¼ Uðxb̂ 3 þ â1 �y1 þ â2 �y2Þ� Uðxb̂ 3 þ â2 �y2Þ ð5Þ
ATEðy4Þ¼ Uðxb̂ 4 þ ĉ1 �y1 þ ĉ2 �y2Þ� Uðxb̂ 4 þ ĉ2 �y2Þ ð6Þ
where x represents the vectors of the means values of the
explanatory variables.
9
3.2 Statistical Tests
To validate the empirical specification, two statistical tests are
conducted: weak instru-
ments test and test for endogeneity. The endogeneity issue
arises if the error terms of the
simultaneous-equation mixed model are correlated. The
endogeneity test also justifies the
need to estimate the four equation system simultaneously. Since
this equation system is
estimated by the maximum likelihood estimation method, a
likelihood ratio test can be
9

64. The interpretation of the treatment effect is similar to the
continuous outcome variable case discussed on
page 787–788 in Greene (2003). However, it is of note that the
average treatment effect in our case is the
differences in the predicted probability, instead of the expected
values as the continuous variable case.
Childhood Obesity and Unhappiness 267
123
used to test if all of the error correlations are exogenous.
Specifically, the null hypothesis is
that all of the estimated correlation coefficients are equal to
zero. The test statistic follows
the chi-square distribution with degree of freedom 6 in our case.
Unlike the two-stage estimation procedure of the instrumental
variable method for
which exclusion conditions are necessary for model
identification, the identification cri-
teria are met due to the nonlinear functional form and
distributional assumption for the
current mixed system (i.e., Eq. 4). However, some exclusion
restrictions are useful to
avoid full reliance on the functional form nonlinearity for
identification.

65. 10
In this study,
mother’s fast food and soft drink consumption are selected as
the exclusion variables in
children’s body weight and unhappiness equations. To validate
our exclusion variables,
the weak instruments test is conducted to investigate if the
excluded variables have
enough explanatory power for model identification. Although
most of the applications of
the weak instrument tests proposed by Staiger and Stock (1997)
are for the linear model,
Kan (2007) provided a modification to a non-linear model.
Using a similar strategy in Kan
(2007), the weak instruments test involves estimating the binary
tobit model for children’s
fast food or soft drink consumption and testing if the excluded
instruments (i.e., mother’s
consumption of fast food and soft drink beverage) have enough
explanatory power. A
likelihood ratio test is implemented and the test statistic follows
a chi-square distribution
(say x2) with the degree of freedom M (2 in our case). To be
consistent with Staiger and

66. Stock (1997), the likelihood ratio test statistic can be covered
with a F statistic as:
x2=M �FðM;1Þ.11
4 Empirical Results
The estimations of the mixed simultaneous equation system and
the results of the statistical
tests are exhibited in Table 3. We begin our discussion of the
results by looking at the
findings of the statistical tests (the bottom in Table 3). Since
mother’s fast food and soft
drink consumption are used as exclusion variables that directly
affect children’s con-
sumption of these two food items, but not directly affect the
risk of being overweight and
unhappiness of children, a statistical test is conducted to see if
these exclusions are sta-
tistically weak. The weak instrument test is conducted
separately for children’s fast food
consumption and soft drink equation. The results of the tests are
encouraging. The values
of the likelihood tests are 42.17 and 33.22 for children’s fast
food and soft drink equations,
respectively. These are asymptotically equal to 21 and 17 of the
F statistics,12 and both of
which are higher than 10 (the critical value) proposed by

67. Staiger and Stock (1997).
Therefore, we may conclude that mother’s fast food and soft
drink consumption are sta-
tistically strong to identify her children’s fast food and soft
drink consumption.
As in the conventional simultaneous equation system, error
correlations accommodate
endogeneity between equations (Amemiya 1973). The
investigation of the correlations of
children’s fast food, soft drink consumption, overweight, and
unhappiness are also of
interest since it could justify the need to estimate a mixed
system. A likelihood ratio
test is conducted to investigate if these correlations are
statistically equal to zero
10
Discussions of the model identification through the nonlinear
functional form are on page 121 in Maddala
(1983).
11
A detailed discussion of the proposed test procedure can be
found on page 71–72 in Kan (2007).
12
The asymptotic statistics of the likelihood ratio test to the F test
is discussed in Kan (2007).

68. 268 H.-H. Chang, R. M. Nayga Jr.
123
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Childhood Obesity and Unhappiness 269
123
T

101. a
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270 H.-H. Chang, R. M. Nayga Jr.
123
(i.e., uncorrelated). The result of the likelihood ratio test is 283,
which is higher than the
conventional significance level of the chi-squared distribution
(x2(0.95,6) = 12.95).
Therefore, this result is supportive of the joint estimation of a
mixed system to improve the
efficiency of the estimators. Additionally, the estimated
correlation coefficient between
child’s fast food and soft drink consumption is 0.277, and it is
statistically significant. This
shows that fast food and soft drink consumption are positively
correlated due to common
unobserved characteristics. Additionally, 8.5 and -6.8%
correlations are found between
child’s fast food consumption and the risk of being overweight
and unhappiness, respec-

128. tively. These results indicate that fast food consumption of
children is associated with risk
of being overweight and unhappiness due to unobserved factors.
Similar evidence is
revealed between child’s soft drink consumption and being
overweight or obese (20.7%).
4.1 Factors Associated with Children’s Fast Food and Soft
Drink
The variables that significantly influence children’s fast food
and soft drink consumption,
overweight, and unhappiness include mothers’ food
consumption, children and family
characteristics, and geographical or regional factors. To begin,
we first examine the factors
that are associated with child’s consumption of fast food and
soft drinks. Results point out
that mother’s fast food and soft drink consumption positively
contributes to children’s food
consumption. This result may not be inconsistent with the belief
that mothers have some
control on children’s food choice, or may reflect the fact that
mothers usually spend more
time than other family members on children’s food consumption
(e.g., Lindsay et al. 2006).

129. Children’s characteristics also affect their food consumption.
For instance, children’s
age is positively correlated with their consumption of fast food
and soft drink. Also,
children who have regular dental examinations consume more
fast food and soft drink than
those who do not have regular dental examinations. Household
characteristics also play an
important role on children’s fast food consumption. Compared
to those in lower income
households, children living in households with income between
NT$50,000 and NT$
70,000 are more likely to consume soft drinks.
Finally, geographical and locational variables also significantly
affect children’s food
consumption. Compared to children living in small towns (the
reference group), children
who live in city and county areas consume more fast food and
soft drinks. This may reflect
the fact that children living in city areas have easy access to
convenience stores or res-
taurants that provide fast food and soft drink, which increases
the frequency of
consumption. It is also no surprise that fast food consumption is

130. lower on children living in
households located in eastern Taiwan. Compared to the north
part of Taiwan (reference
group), eastern Taiwan has less business and commercial
activities. Therefore, the fast
food consumption of children may be lower due to the limited
availability of fast food
restaurants.
4.2 Factors Associated with Children’s Overweight and
Unhappiness
Perhaps, the most interesting finding and contribution of this
paper is the association
between children’s fast food and soft drink consumption, and
their objective and subjective
wellbeing. Results show that children who consume more fast
food and soft drink are more
likely to be overweight but are less likely to be unhappy. The
estimated average treatment
effects of children’s fast food and soft drink on overweight are
0.02 and 0.151. That is,
after controlling for the socioeconomic factors and other
exogenous determinants,
Childhood Obesity and Unhappiness 271

131. 123
compared to children who don’t consume these two food
products, those children have
more likely to be overweigh by 2 and 15%, respectively.
However, those children have 5
and 4.6% lower probabilities of being unhappy. Several points
are noticeable from this
finding. First, this result is continuing to confirm the findings
of previous studies regarding
the positive association between children fast food consumption
and body weight (e.g.,
Chen et al. 2006). Second, this finding contributes to the debate
of the influences of
children’s soft drink consumption on body weight. Consistent
with the findings in Troiano
et al. (2000), a positive association between soft drinks
consumption and the risk of being
overweight or obese is evident. Third, our results demonstrate
that children’s consumption
of fast food and soft drink are positively correlated with their
happiness.
Other factors that are significantly associated with children’s
weight status include the

132. characteristics of children, household, and geographical and
regional conditions. For
example, compared to children living in lower income
households, children who live in
households with family income between NT$70,000 and
NT$100,000 are less likely to be
overweight or obese. This result is consistent with the finding
in Anderson et al. (2003)
using the NHANES 1988–1994 data in the United States.
Household characteristics also
influence children’s likelihood of being overweight and obese.
Results indicate that chil-
dren living in households with at least one member needing long
care medical service are
less likely to be overweight or obese. Regions and geographic
variables also significantly
determine children’s body weight. Compared to children living
in the north part of Taiwan,
children who live in households located in the southern part
have higher risk of being
overweight or obese.
Factors that determine children’s unhappiness are similar to the
findings of the weight

133. status. Consistent with the findings in previous studies
indicating the importance of the
association between children’s age and the psychological/mental
health (e.g., Frey and
Stutzer 2002), results show that child’s age is negatively
associated with their happiness.
Consistent with the finding of factors determining children body
weight, children living in
households with long care family members are more likely to
feel unhappy, sad or
depressed. Urbanization and geographic locations are also
significant determinants of
children’s happiness. Compared to children who live in the rural
area, those who live in the
city or county areas have higher propensity to be unhappy. This
may reflect the envi-
ronmental effects of living in a city than in a rural area (e.g.,
pollution, noise, security,
etc.). The effects of environmental factors on children’s
subjective wellbeing can be further
confirmed by the finding that, compared to children in the
northern area of Taiwan,
children living in the eastern part of Taiwan are found to be less
unhappy.

134. 5 Concluding Remarks
Extensive literature has examined the factors that are associated
with children’s objective
wellbeing (i.e., body weight), but relatively little is known
about children’s subjective
wellbeing (i.e., unhappiness). Focusing on children’s
consumption of fast food and soft
drink, this paper investigates the association between children’s
fast food and soft drink
consumption, and the risk of being overweight and unhappy. No
other known study has
evaluated the effect of fast food and soft drinks consumption on
children’s obesity and
unhappiness. Moreover, in contrast to previous studies, we
estimate a mixed system
allowing for the endogeneity between children’s food
consumption and wellbeing.
Using a nationwide survey data in Taiwan, our results show that
children’s character-
istics and household factors, as well as the geographical
conditions, are associated with
272 H.-H. Chang, R. M. Nayga Jr.
123

135. children’s consumption of fast food and soft drinks.
Specifically, mother’s fast food and
soft drinks consumption behavior is found to be positively
associated with their children’s
fast food and soft drinks consumption. In our analysis, the error
correlations between fast
food and soft drink consumption, and children’s weight status
and happiness are significant
and interrelated. Therefore, it is necessary to estimate these
equations simultaneously. With
respect to the effects of children’s fast food and soft drink
consumption on children’s
wellbeing, our results suggest a trade-off in the influence of
food consumption on child-
hood obesity and unhappiness since while consumption of fast
food and soft drinks is
positively associated with childhood obesity, they also tend to
make them less unhappy.
This finding is of particular policy interest since current policy
strategies for decreasing the
prevalence of childhood obesity have focused on child’s
objective wellbeing (e.g., body
weight), and far less attention has been paid to the examination

136. of the subjective wellbeing.
Interestingly, our results also imply that consumption of fast
food and soft drinks is
negatively correlated with degree of unhappiness. While the
definitive assessment of the
mechanisms underlying these associations is complicated, these
findings may imply that
there could be a tradeoff between children’s obesity and
happiness with reductions in fast
food and soft drink consumption. It is then possible that policy
interventions would be
insufficiently effective in reducing childhood obesity if they do
not take into account the
effect of policy prescriptions such as reducing fast food and soft
drinks consumption on
children’s happiness. Policy or program prescriptions should
take this tradeoff into account
to facilitate reduction in childhood obesity without sacrificing
children’s degree of hap-
piness. Hence, current and future policy/program interventions
that aim to decrease fast
food and soft drinks consumption of children to reduce
childhood obesity may be more
effective if these interventions also focus on ways that could

137. compensate the potential
reduction in degree of happiness of children.
Future research should accommodate the other types of food
items (e.g., fruit and
vegetable etc.) that may increase children’s happiness but at the
same time may not
increase body weight. However, including more items of food
consumption is chal-
lenging in model estimation. One caveat from our analysis is
that due to data limitations,
our measure for food consumption is based on frequency scores
and not actual amount
consumed by children and our measure for degree of children’s
unhappiness is based on
subjective observations from parents. In addition, we could not
include an exercise
variable in our model due to data limitations. Admittedly, the
addition of an exercise
variable may moderate the effects of fast food and soft drink
consumption in the
analysis. Hence, future research should replicate our analysis
with more measures related
to exercise and other lifestyle behaviors to test the robustness of
our findings. With data

138. availability, the addition of psychological factors should also be
included in the analysis
to further assess the robustness of our findings. For example,
consumption of fast food
and soft drink may be addictive or may lead to depression and
feeling of being
exhausted. If this is the case, then it is possible that
consumption of fast food and soft
drink may just be a temporary relief from an addiction and may
then not be associated
with a true happy feeling.
Acknowledgments Hung-Hao Chang acknowledges partial
funding support from the National Science
Counsel of Taiwan under Grant No: 95-2415-H-002-041. The
data used in the analysis is provided by the
Bureau of Health Promotion, Department of Health and National
Health Research Institute in Taiwan. The
interpretation and conclusions do not represent those of
Department of Health and National Health Research
Institute. The authors accept responsibility for any remaining
errors or omissions.
Childhood Obesity and Unhappiness 273
123
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