ArticlePDF AvailableLiterature Review

Fast Food Pattern and Cardiometabolic Disorders: A Review of Current Studies

Authors:

Abstract

Background: There are growing concern globally regarding the alarming trend of fast food consump­tion and its related cardiometabolic outcomes including overweight and obesity. This study aimed to review the current evidences available in relation to adverse effects of fast food pattern on cardiometa­bolic risk factors. Methods: Relevant articles including epidemiological and clinical studies with appropriate design and good quality were obtained through searches of the Medline, PubMed, Scopus databases and Google scholar with related key words including "fast foods", "processed foods", "obesity", "overweight", "insulin resistance", "diabetes", "cardiovascular disease", "metabolic syndrome", "dyslipidemia" and "hypertension". Results: Fast food consumption and out-of-home eating behavior is a main risk factor for lower diet quality, higher calorie and fat intake and lower micronutrients density of diet. Frequent consumption of fast foods was accompanied with overweight and abdominal fat gain, impaired insulin and glucose homeostasis, lipid and lipoprotein disorders, induction of systemic inflammation and oxidative stress. Higher fast food consumption also increases the risk of developmental diabetes, metabolic syndrome and cardiovascular disease. Conclusion: This review provides further evidence warning us against the irreparable effects of fast food consumption on public health especially the increasing global burden of obesity and cardiovascu­lar diseases.
231
Health Promotion Perspectives, 2015, 5(4), 231-240
doi:10.15171/hpp.2015.028
http://journals.tbzmed.ac.ir/HPP
Fast Food Pattern and Cardiometabolic Disorders: A Review of Current Studies
Zahra Bahadoran1,*Parvin Mirmiran1, Fereidoun Azizi2
1 Nutrition and Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences,
Tehran, Iran
2Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
ARTICLEINFO
ABSTRACT
Article history:
Received: Mar 01 2015
Accepted: Oct 04 2015
e-published: Jan 30 2016
Background: There are growing concern globally regarding the alarming trend of fast food consump-
tion and its related cardiometabolic outcomes including overweight and obesity. This study aimed to
review the current evidences available in relation to adverse effects of fast food pattern on cardiometa-
bolic risk factors.
Methods: Relevant articles including epidemiological and clinical studies with appropriate design and
good quality were obtained through searches of the Medline, PubMed, Scopus databases and Google
scholar with related key words including “fast foods”, “processed foods”, “obesity”, “overweight”,
“insulin resistance”, “diabetes”, “cardiovascular disease”, “metabolic syndrome”, “dyslipidemia” and
“hypertension”.
Results: Fast food consumption and out-of-home eating behavior is a main risk factor for lower diet
quality, higher calorie and fat intake and lower micronutrients density of diet. Frequent consumption of
fast foods was accompanied with overweight and abdominal fat gain, impaired insulin and glucose
homeostasis, lipid and lipoprotein disorders, induction of systemic inflammation and oxidative stress.
Higher fast food consumption also increases the risk of developmental diabetes, metabolic syndrome
and cardiovascular disease.
Conclusion: This review provides further evidence warning us against the irreparable effects of fast
food consumption on public health especially the increasing global burden of obesity and cardiovascu-
lar diseases.
Keywords:
Fast food, Obesity,
Metabolic syndrome,
Insulin resistance,
Cardiovascular disease,
Diabetes
*Corresponding Author:
Parvin
Mirmiran
Shahid Beheshti University of
Medical Sciences
Tel: +98 21 223 57 484;
e-mail:
Parvin.mirmiran@gmail.com
Introduction
A growing trend of fast food consumption
along with alarming trend of cardiometabolic dis-
orders is considered as a globally health problem.
Although there is no agreement on the definition
of fast food, it is mainly defined as "easily pre-
pared processed food served in snack bars and
restaurants as a quick meal or to be taken away" in
dictionaries and encyclopedias; industrial foods
such as canned foods or snacks may also consid-
ered as fast foods.1In the recent years, an increas-
ing globally popularity have been developed re-
garding the fast foods and take-away foods mar-
keting. Out-of-home meals and fast foods are rich
in highly processed meat and refined carbohydrate,
sodium, total fat, saturated and trans fatty acids,
cholesterol, and poor in essential nutrients and
dietary fibers; 2 the fast food pattern also has un-
desirable effects on overall diet quality especially
in children and adolescents.2-4Fast food consump-
tion and out-of-home eating behavior is a main
risk factor for higher calorie and fat intake and
lower micronutrients density of diet.3,5 Frequent
consumption of fast foods is one of the main rea-
sons for rising trends of overweight and obesity,
cardiovascular disease, type 2 diabetes and other
metabolic abnormalities.3,6-8Higher availability of
fast food services is associated with higher mortal-
ity and hospital admission rates for acute coronary
heart disease as well as a higher risk of overweight
and obesity.9,10
Considering to growing interest to Western di-
etary patterns and trend of fast food consumption
Review Article
Health Promotion Perspectives, Vol. 5, No. 4, 2015; P:231-240
232
along with global burden of cardiovascular diseas-
es, diabetes, obesity and hypertension, and the
lack of a comprehensive review study on cardi-
ometabolic outcomes of these dietary patterns,
this study aimed to review the current evidence in
relation to adverse effects of fast food patterns on
non-communicable diseases with focusing on car-
diometabolic risk factors.
Materials and Methods
This is a narrative review article. The original
research articles were reviewed published in Eng-
lish from 1990 to 2014. To search the articles, a
number of databases and search engines, including
PubMed, Medline, Scopus and Google Scholar
were used. The references of the articles were also
reviewed to identify papers that are more relevant.
Searches were conducted with the search terms
“fast foods”, “processed foods”, “obesity”, “over-
weight”, “insulin resistance”, “diabetes”, “cardio-
vascular disease”, “metabolic syndrome”, “dyslip-
idemia” and “hypertension”. Relevant articles in-
cluding both epidemiological including cohort,
case-control, cross-sectional and clinical studies
were assessed for initial eligibility. Studies with
English language evaluated the association be-
tween fast food consumption with cardiometa-
bolic risk factors, with appropriate design and
good quality (e.g. accurate definition of exposure
and outcome, study population, clearly defined
statistical methods) were included.
Ethical consideration
Ethical issues which have been considered for
this study was included prevention of selective
reporting bias of the papers, and honesty in re-
porting of the results of the studies. Moreover,
related references have been carefully cited
throughout the manuscript.
Results
Fast food consumption and the risk of over-
weight and obesity
The alarming trend in the acceleration of over-
weight and obesity is mainly attributed to changes
in lifestyle determinants and environmental fac-
tors. A rapid on-going nutrition transition with
progressive shift to a westernized diet, in particu-
lar higher consumption of industrial and pro-
cessed foods, and sweetened beverages are major
factors contributing to the global epidemic of obe-
sity.11 Among various dietary factors, out-of-home
eating patterns and regular consumption of fast
food have been proposed as determinant factors
in the prevalence of obesity and severe weight
gain over time;12,13 an association which has been
confirmed in both prospective and cross-sectional
studies. In Table 1, the associations of fast food
consumption with anthropometric measures and
risk of obesity in cohort and cross-sectional stud-
ies were reviewed.
Frequent consumption of fast food, ≥2
times/week, compared to <1 time/week, has been
accompanied with ≥4.5 kg weight gain during a
fifteen-year follow-up of US adolescents and
young adults.6
Participants of the Coronary Artery Risk De-
velopment in Young Adults (CARDIA) study
who were in the highest compared to the lowest
quartile of fast food consumption, had higher
weight (adjusted mean=5.6 kg, 95% CI= 2.1-9.2),
and waist circumference (adjusted mean=5.3 cm,
95% CI=2.8-7.9) after a 13-yrfollow-up; in this
study, fast food intake was associated with 13-yr-
changes in body weight (β=0.15, 95% CI= 0.06-
0.24) and waist circumference (β=0.12, CI= 0.04-
0.20).7 A3-yrfollow-up of adults also showed that
increased consumption of fast foods was associ-
ated with an increase in body mass index(BMI)
change (β=0.05, 95% CI=0.01-0.09); each one
unit increase in fast food consumption (1 time/wk)
was associated with a 0.13 increase in BMI at
baseline (β= 0.13, 95% CI: 0.04-0.22) and a 0.24
increase in BMI after 3years (β=0.24, 95% CI=
0.13-0.34).14
Participants of the Coronary Artery Risk De-
velopment in Young Adults (CARDIA) study
who were in the highest compared to the lowest
quartile of fast food consumption, had higher
weight (adjusted mean=5.6 kg, 95% CI= 2.1-9.2),
and waist circumference (adjusted mean=5.3 cm,
95% CI=2.8-7.9) after a 13-yrfollow-up; in this
study, fast food intake was associated with 13-yr-
Bahadoran et al.: Fast Food Pattern and Cardiometabolic Disorders
233
changes in body weight (β=0.15, 95% CI= 0.06-
0.24) and waist circumference (β=0.12, CI= 0.04-
0.20).7 A3-yrfollow-up of adults also showed that
increased consumption of fast foods was associ-
ated with an increase in body mass index (BMI)
change (β=0.05, 95% CI=0.01-0.09); each one
unit increase in fast food consumption (1 time/wk)
was associated with a 0.13 increase in BMI at
baseline (β= 0.13, 95% CI: 0.04-0.22) and a 0.24
increase in BMI after 3 years (β=0.24, 95% CI=
0.13-0.34) .14
Table 1: The association of fast food consumption with anthropometric measures and the risk of obesity in cohort and cross-
sectional studies
Author
Design, study population and sample size
Findings
Fifteen-year follow-up of US adolescents and
young adults, n= 3031
Consumption of fast food, 2 times/week, compared to <1 time/week
was accompanied with 4.5 kg more weight gain
Pereira et al.,
2005 (6)
Thirteen-year follow-up of young adults par-
ticipated in CARDIA study, n= 3643
Highest compared to the lowest quartile of fast food consumption was
accompanied with higher weight and waist circumference
Duffey et al.,
2009 (7)
Three-year follow-up of adults, n=3394
Increased consumption of fast foods (>1 time/wk) increased body mass
index.
Duffey et al.,
2007 (14)
Two-year follow-up of adults participants in
Mediterranean cohort study, n= 7194
More consumption of hamburger, pizza, and sausages increased risk of
weight gain (3 kg during a 5 past year) (OR=1.2, 95% CI=1-1.4)
Bes-Rastrollo
et al., 2006 (15)
Cross-sectional study of school children,
n=1033
Higher consumption of fast food was associated with higher BMI Z score
(β=0.08, 95% CI=0.03-0.14), higher body fat (β=2.06, 95% CI=1.33-2.79)
and an increased risk of obesity (OR=1.23, 95% CI=1.02-1.49).
Jeffery et al.,
2006 (17)
Cross-sectional study of Singaporean adults,
n=1627
The risk of abdominal obesity was 1.24 (95% CI=1.03- 1.51) and 1.52
(95 % CI= 1.32- 1.77) in regular consumers and occasional consumers of
fast foods.
Whitton et al.,
2013 (19)
A cross-sectional study of adults participated
in Michigan Behavioral Risk Factor Survey
Increased risk (OR=1.81, 95% CI=1.35-2.44) of obesity was observed in
adults with consuming 3 times/week compared to <1 time/week fast
foods.
Anderson et
al., 2011 (20)
A cross-sectional study of Iranian men and
women participated in Tehran Lipid and Glu-
cose Study, n=1944
A significant association was observed between fast food intake and BMI
(β=0.104, P<0.01) as well as waist circumference (β=0.083, P<0.01).
Bahadoran et
al., 2012 (2)
A cross-sectional survey on adults resident in
Michigan, n=1345
A significant association was found between local concentrations of fast
food outlets with body mass index (β=3.21, P<0.001) and poor diet quali-
ty (β=2.67, P<0.008).
In a Mediterranean cohort study, a higher risk
of weight gain (≥3 kg during a 5 past year)
(OR=1.2, 95% CI=1-1.4) was observed in adults
who consumed more hamburger, pizza, and sau-
sages; a significantly greater weight gain during a
2-year follow-up was also observed in the highest
compared to the lowest quintile of fast food con-
sumption (0.77 kg vs. 0.47 kg).15 A three-year fol-
low-up of women also indicated that increased
consumption of one fast food meal per week led
to a 0.72 kg more weight gain.21
Cross-sectional studies2,16-20,22 also reported a
positive association between consumption of fast
food and the anthropometric measures in differ-
ent populations and various age-groups; in school
children, consumption of fast food was associated
with a higher BMI Z-score (β=0.08, 95%
CI=0.03-0.14), higher body fat (β=2.06, 95%
CI=1.33-2.79) and an increased risk of obesity
(OR=1.23, 95% CI=1.02-1.49). In a cross-sec-
tional survey, frequency of fast food consumption
was positively associated with body mass index
(β=0.31, P=0.02), in adults.16 The association of
fast foods and BMI was β=0.39 and 0.85 in high-
and low-income in young and middle-aged wom-
en, respectively.22 In Singaporean adults, the risk
of abdominal obesity was 1.24 (95% CI=1.03-
1.51) and 1.52 (95 % CI= 1.32- 1.77) in regular
consumers and occasional consumers of fast food
meals.17 In the Michigan Behavioral Risk Factor
Survey, the adjusted-odds of obesity in adults con-
suming ≥3 times/week compared to <1
time/week fast food meals was 1.81 (95%
CI=1.35-2.44).18 A significant association between
fast food intake and BMI (β=0.104, P<0.01) as
well as waist circumference (β=0.083, P<0.01) was
observed among Iranian young adults.19 In Medi-
terranean adults, the association of fast food con-
Health Promotion Perspectives, Vol. 5, No. 4, 2015; P:231-240
234
sumption with BMI was estimated to be β=1.76
(95% CI=0. 22, 3.3), and the risk of obesity in-
creased by 129% in >1 time/week fast food con-
sumers, compared to non-consumers.2 More in-
terestingly, a health community survey in Michi-
gan found a significant association between local
concentrations of fast food outlets with BMI
(β=3.21, P<0.001) and poor diet quality (β=2.67,
P<0.008).20
Findings of a study on 23182 adolescents in
Finland showed an strong association between
fast-food outlet near school with breakfast skip-
ping and undesirable eating habits; in this study,
proximity of a fast-food outlet was associated with
increased risk of overweight (OR=1.25, 95%
CI=1.03-1.52).23 One study on the participants of
National Health and Nutrition Examination Sur-
vey showed that fast food and full-service restau-
rant consumption, respectively, was associated
with more energy, total fat and sodium intake as
well as a decrease in daily intake of vitamin A, D,
and K.24 Fast-food consumption was also signifi-
cantly associated with higher intake of total energy
(β=72.5, P=0.005), empty calories (β=0.40,
P=0.006) and BMI (β=0.73, P=0.011), and lower
healthy eating index score (β= -1·23, P=0·012),
vegetables (β=-0·14, P=0·004), whole grains (β=-
0.39, P=0·005), fiber (β= -0.83, P=0·002), magne-
sium (β=-6·99, P=0·019) and potassium intakes
(β=-57.5, P=0·016).25
Fast food consumption and dyslipidemia
Another cardiometabolic risk factor regarding
fast food pattern highlighted in the literature is
impaired metabolism of lipids and lipoproteins. In
Coronary Artery Risk Development in Young
Adults (CARDIA), participants who consumed
≥2.5 compared to <0.5 meal/week of fast food
meals, had higher levels of serum triglycerides
(117±3.6 mg/dl vs. 95±5.2 mg/dl), and lower
high-density lipoprotein cholesterol (HDL-C)
(52.0±0.7 mg/dl vs. 57.5±1.1 mg/dl), over 13
years of follow-up; moreover, longitudinal associa-
tions (β coefficient ± SE) of weekly fast food con-
sumption with 13-year changes of triglycerides
(TG), low-density lipoprotein cholesterol (LDL-C)
and HDL-C were β=0.24±0.40, β=0.16±0.14, and
β=0.08±0.06), respectively.7 A greater increase in
3-year changes of TG levels was found in Tehran
Lipid and Glucose Study (TLGS) participants,
who consumed more fast food meals at baseline
(10.6% vs. 4.4% increase, in the fourth compared
to first quartile of fast food intake); serum triglyc-
erides to HDL-C ratio, an independent risk factor
of cardiovascular disease, also increased in adults
with higher compared to lower fast food intakes
(3.7% vs. -5.5%, in the fourth compared to the
first quartile).8
A cross-sectional analyses in TLGS study also
indicated that fast food consumption (g/week)
was significantly associated with serum TG
(β=0.07, P<0.05), HDL-C (β= -0.05, P<0.05) and
atherogenic index of plasma (β=0.06, P<0.05) on-
ly in middle-age adults; a higher prevalence of hy-
pertriglyceridemia was also observed in the high-
est compared to the lowest tertile of fast foods
(42.3 vs. 34.2%).19 Postprandial lipemia and lipid
peroxidation increased after consumption of a fast
food meal, compared to a healthy meal; triglyc-
eride levels, malondialdehyde, and thiobarbituric
acid reactive substances (TBARS) were signifi-
cantly higher and HDL-C levels were significantly
lower after fast food meal.26
Fast food consumption and the risk of diabe-
tes, metabolic syndrome and cardiovascular
disease
The adverse effects of fast foods consumption
on the development of metabolic abnormalities
has been reported in several investigations. The
associations of fast food consumption with the
risk of insulin resistance, diabetes, metabolic syn-
drome and cardiovascular disease in cohort and
cross-sectional studies were summarized in Table2.
A 15-yrfollow-up of American women showed
that higher fast food intake 2 times resulted in
greater insulin resistance.6 In the CARDIA Study,
participants in the 3rd and 4th, compared to the
first quartile category, of fast food intakes at base-
line, had greater odds of metabolic syndrome after
13-yrof follow-up (OR= 1.9, 95% CI= 1.11-3.26
and OR= 2.14, 95% CI= 1.24-3.70, in 3rd and 4th
quartiles, respectively); homeostatic model assess-
ment of insulin resistance (HOMA-IR) at final
Bahadoran et al.: Fast Food Pattern and Cardiometabolic Disorders
235
examination was also positively associated with
fast food consumption at baseline (3.9±0.14
vs.0.3±0.18 in the highest compared to the lowest
quartile of fast foods).A one-follow-up of adults
showed that higher consumption of processed
meat products was independently associated with
the incidence of metabolic syndrome (OR= 2.5,
95% CI= 1.0-6.2).30
Table2: The association of fast food consumption with the risk of insulin resistance, diabetes, metabolic syndrome and cardiovas-
cular disease in cohort and cross-sectional studies
Author
Design, study population and sample size
Findings
Pereira et al., 2005 (6)
Fifteen-year follow-up of American women,
n=3031
Consumption of fast foods 2 times/week increased the risk
of insulin resistance.
Duffey et al., 2009 (7)
Thirteen-year follow-up of adults participated
in CARDIA study, n=36.43
Higher consumption of fast foods increased the risk of meta-
bolic syndrome (OR= 1.9, 95% CI= 1.11-3.26) and (OR= 2.14,
95% CI= 1.24-3.70), in the 3rd and 4th quartiles, respectively).
Higher insulin resistance index was observed in the highest
compared to lowest quartile of fast foods (3.9±0.14 vs.
0.3±0.18, P<0.05).
Duffey et al., 2007 (14)
One-year follow-up of adults, n=3394
Higher consumption of processed meat products was associ-
ated with the incidence of metabolic syndrome (OR= 2.5, 95%
CI= 1.0-6.2).
Bahadoran et al., 2013 (8)
Three-year follow-up of men and women
participated in Tehran Lipid and Glucose
Study, n=1476
The higher compared with the lower quartile of fast foods con-
sumption increased the risk of metabolic syndrome by 85%
(OR=1.85, 95% CI=1.172.95).
Odegaard et al., 2012 (29)
Follow-up of Singaporean women, n= 43 176
for diabetes and n=52 584 for coronary heath
disease mortality
Consumption of fast food 2 times/week increased the oc-
currence of type 2 diabetes (hazard ratio= 1.27, 95% CI= 1.03-
1.54) and coronary heart disease mortality (hazard ratio = 1.56,
95% CI= 1.18-2.06).
Halton et al., 2006 (30)
Twenty-year follow-up of women participated
in Nurses' Health Study, n=84 555
Higher intake of French fries increased the risk of diabetes by
21% (OR=1.21, 95% CI=1.09-1.33).
Krishnan et al., 2010 (31)
Ten-year follow-up of women participated in
Black Women's Health Study, n=44 072
Higher intake of hamburgers and fried chicken ( 2
meals/week compared to none) increased incidence rate of type
2 diabetes by 1.40 (95% CI= 1.14, 1.73) and 1.68 (95% CI=
1.36, 2.08), respectively.
Alter et al., 2005 (9)
Cross-sectional survey in Canada, n=380
regions
The higher compared to the lower accessibility to fastfood
services increased the risk of mortality (OR= 2.52, 95%
CI=1.54-4.13) and acute coronary hospitalizations (OR= 2.62,
95% CI=1.42-3.59).
The prospective approach of TLGS also
showed that the risk of metabolic syndrome in the
highest, compared with the lowest, quartile of fast
foods increased by 85% (OR=1.85, 95%
CI=1.172.95); in this study, the adverse effects of
fast food consumption were more pronounced in
younger adults (<30 yr), and participants who had
greater waist to hip ratio, consumed less phyto-
chemical-rich foods or had low-fiber diet
(P<0.05).8 Non-alcoholic fatty liver disease, a he-
patic feature of metabolic syndrome, could be a
result of fast food consumption. In an interven-
tion study, 4-wkconsumption of fast food meals
(≥2meals/day) in healthy subjects increased serum
levels of alanin aminotransferase (22.1±11 U/l to
69.3±76 U/l), insulin resistance index (0.89±0.42
to 1.6±0.83) and hepatic triglyceride content
(1.1±1.9% to 2.8±4.8%) as well as body fat per-
cent (20.1±9.8% to 23.8±8.6%).31
A prospective cohort of Singaporean women
showed that consumption of fast food ≥2
times/wk increased the occurrence of type 2 dia-
betes (hazard ratio= 1.27, 95% CI= 1.03-1.54) and
coronary heart disease mortality (hazard ratio =
1.56, 95% CI= 1.18-2.06).27
Increased consumption of burger, fried chick-
en meals, sausage and other processed meat prod-
ucts as well as French fries was associated with an
increased risk of developing type 2 diabetes melli-
tus; a prospective study of 84,555 women in the
Nurses' Health Study indicated that higher intake
of French fries increased the 20-years risk of dia-
betes by 21% (OR=1.21, 95% CI=1.09-1.33).28In
Black Women's Health Study, the 10-year inci-
Health Promotion Perspectives, Vol. 5, No. 4, 2015; P:231-240
236
dence rate of type 2 diabetes for higher intake of
hamburgers and fried chicken (≥ 2 meals/week
compared to none) was 1.40 (95% CI= 1.14, 1.73)
and 1.68 (95% CI= 1.36, 2.08), respective-
ly.29Meta-analysis of seven prospective cohorts
found that higher consumption of processed meat
increased the risk of type 2 diabetes by 19% (95%
CI=1.11-1.27).32
More interestingly, rather than the consump-
tion of fast foods, the rate of accessibility to fast
food services has been reported as a risk factor for
cardiovascular disease; risk-adjusted outcomes in
regions with high compared to low accessibility to
fast food services were greater for mortality (OR=
2.52, 95% CI=1.54-4.13) and acute coronary hos-
pitalizations (OR= 2.62, 95% CI=1.42-3.59).9
Discussion
This review provides further evidence warning
us against the irreparable effects of fast food con-
sumption on public health especially the increas-
ing global burden of obesity and cardiovascular
diseases. Frequent consumption of fast foods as
well as out-of-home meals is a serious dietary risk
factor for development of increasing trend of obe-
sity and other related abnormalities. Higher con-
sumption of fast foods has undesirable effects on
dietary intake and overall diet quality, which leads
to increased incidence of metabolic disorders in-
cluding obesity, insulin resistance, type 2 diabetes
as well as cardiovascular disorders.
Briefly, compared to non-consumers or <1
time/week, regular consumption of fast foods and
out-of-home meals ≥1-3 times/week was associ-
ated with an 20-129%elevated risk of general and
abdominal obesity.9,15,17,18Increased risk of type 2
diabetes and metabolic syndrome in subjects with
higher consumption of fast foods (mean 2
times/week) was reported 27-68% and 85-150%,
respectively.7,8,14,27-29 Higher consumption of fast
foods and higher exposure to multiple sources of
accessible, cheap, energy-dense fast foods were
also accompanied with a 56-162% increased risk
of coronary heart disease mortality.9,27
Several possible mechanisms have been sug-
gested to explain undesirable effects of fast foods
on health status. A main factor describing the
obesity-induced properties of fast foods is a high-
energy dense modality. Most fast foods have an
extremely high energy density, approximately 158
to 163 kcal per 100 gram of food; it also has been
estimated that a fast food meal typically has an
energy density twice the recommended a healthy
diet and contains approximately 236 kcal/100 g.33
High energy density of foods may have adverse
effects.34 In children, consumption of fast foods
compared to non-consumers, led to greater intake
of energy (>187 kcal/day), energy density (0.3
kcal/g), total fat (9g/d), carbohydrate (24 g/d),
and added sugar (26g/d). 35 In adults, participants
in the highest compared to the lowest quartile of
fast food consumption also had more energy in-
take (>460 kcal/d), total fat (>2.5% of total en-
ergy), and cholesterol (>30 mg/d).8 The difference
of calorie intake in fast food days, compared with
non-fast food days was estimated to be within 400
kcal in overweight adolescents.36
High-fat content and inappropriate composi-
tion of fatty acids of fast foods is a main dietary
risk for chronic disease. Mean total fat percent of
beef hamburgers, chips, chicken hamburgers and
hot dogs has been reported within 35.83±10.68%,
35.84±8.66%, 23.02±5.07%, and 34.02±13.49%,
respectively; 28-52% of total fat was estimated as
saturated fat.37
Large portion size, high amount of refined car-
bohydrates and added sugar, and high glycemic
load are other characteristics that could explain
the threatening properties of fast food meals.38In
some of the most popular fast foods, trans fats
were up to 24g/serving.4 Higher content of indus-
trially produced trans fatty acids in fast foods is an
important component leading to weight gain, ab-
dominal fat accumulation, development of insulin
resistance and cardiovascular events.39 Further-
more, sodium content of fast foods is often higher
than recommended amounts; in some common
fast food meals, salt content was reported to range
from 4.4 to 9.1 gr per meal;40 a high-salt diet be-
sides increasing blood pressure also intensifies
insulin resistance and metabolic syndrome fea-
tures.41
Bahadoran et al.: Fast Food Pattern and Cardiometabolic Disorders
237
Some of the mechanisms that could explain the
metabolic outcomes of fast foods have been in-
vestigated in clinical and experimental studies.
Postprandial adverse metabolic disorders includ-
ing lipemia, oxidative stress and pro-inflammatory
processes after eating a fast food meal observed in
a human study are other possible explanations for
cardiometabolic outcomes of fast foods.26 Com-
pared to a healthy fast food meal (fiber rich sour-
dough rye bread, salad with vinegar, orange juice),
a hamburger meal (hamburger, bacon, cola drink)
was associated with higher postprandial serum
levels of glucose and insulin.42,43
In animal models, fast food diet induced a phe-
notype of non-alcoholic fatty liver and steatohepa-
titis;43 in this study, fast food diet was accompa-
nied with higher liver weight, serum concentration
of aspartate aminotransferase, intra-acinar in-
flammation and development of steatosis. Higher
expression of genes related to fibrosis, in-
flammation, endoplasmic reticulum stress, and
lipoapoptosis also was induced by fast food diets;
activated pathways of hepatocellular oxidative
stress, profibrotic and pro-inflammatory pathways
were observed.44After a fast food meal, a severe
decrease in plasma antioxidant vitamins including
vitamin A, E and C, and zinc, as well as iron accu-
mulation was observed in rats; decreased levels of
superoxide dismutase, reduced gluthathione, and
higher levels of thiobarbituric acid reactive sub-
stances, lipoprotein oxidation susceptibility, C re-
active protein and tumor necrosis factor-alpha
were also observed.44
This study was a narrative review and had
some limitations, which should be considered;
subjective nature of the search method, potential
selection bias of the articles, probable missing of
unpublished data and lack of using Preferred Re-
porting Items for Systematic Reviews and Meta-
Analyses (PRISMA) to design and report of the
study were the mains limitations. Further re-
searches especially meta-analysis of current studies
may provide a comprehensive and accurate pic-
ture for undesirable outcomes of fast food pat-
terns. Moreover, further assessment of nutritional
behaviors and social determinants of fast foods
intakes among different populations could help to
development of efficient health strategies.
Conclusion
Considering to growing interest to out-of-home
meals and high prevalence of fast food consumption,
food policies with an emphasis on providing healthy
foods, and making nutritional information at fast-
food restaurants may help consumers to order more
healthful or lower-calorie foods.
Acknowledgments
The authors wish to thank Ms. N.Shiva for
critical editing of English grammar and syntax.
Conflict of interest
There is no conflict of interest.
References
1. Definition of fast foods: Oxford dictionaries
[Internet]. Oxford University Press; 2007 [Cited
March 2014]. Available from:
http://www.oxforddictionaries.com/definition/
english/fast-food.
2. Schröder H, Fïto M, Covas MI, REGICOR in-
vestigators. Association of fast food consump-
tion with energy intake, diet quality, body mass
index and the risk of obesity in a representative
Mediterranean population. Br J
Nutr2007;98:1274-1280.
doi: 10.1017/S0007114507781436
3. Rudolph TK, Ruempler K, Schwedhelm E,
Tan-Andresen J, Riederer U, Böger RH, et al.
Acute effects of various fast-food meals on vas-
cular function and cardiovascular disease risk
markers: the Hamburg Burger Trial. Am J Clin-
Nutr2007;86:334-340.
4. Stender S, Dyerberg J, Astrup A. High levels of
industrially produced trans fat in popular fast
foods. N Engl J Med 2006;354:1650 1652.doi:
10.1056/NEJMc052959
5. Lachat C, Nago E, Verstraeten R, Roberfroid
D, Van Camp J, Kolsteren P. Eating out of
home and its association with dietary intake: a
Health Promotion Perspectives, Vol. 5, No. 4, 2015; P:231-240
238
systematic review of the evidence. Obes
Rev2012;13:329-346.
doi:10.1111/j.1467-789X.2011.00953.x
6. Pereira MA, Kartashov AI, Ebbeling CB, Van
Horn L, Slattery ML, Jacobs DR Jr, et al. Fast-
food habits, weight gain, and insulin resistance
(the CARDIA study): 15-year prospective analy-
sis. Lancet2005;365:36-42.doi:10.1016/s0084-
3741(08)70334-2
7. Duffey KJ, Gordon-Larsen P, Steffen LM, Ja-
cobs DR Jr, Popkin BM. Regular consumption
from fast food establishments relative to other
restaurants is differentially associated with meta-
bolic outcomes in young adults. J Nutr2009;
139:2113-2118.
doi:10.3945/jn.109-.109520
8. Bahadoran Z, Mirmiran P, Hosseini-Esfahani F,
Azizi F. Fast food consumption and the risk of
metabolic syndrome after 3-years of follow-up:
Tehran Lipid and Glucose Study. Eur J Clin-
Nutr2013; 67:1303-1309.doi:
10.1038/ejcn.2013.217
9. Alter DA, Eny K. The relationship between the
supply of fast-food chains and cardiovascular
outcomes. Can J Public Health2005;96:173-177.
10. Ledoux T, Adamus-Leach H, O'Connor DP,
Mama S, Lee RE. The association of binge eat-
ing and neighborhood fast-food restaurant
availability on diet and weight status. Public
Health Nutr 2014; 18:352-360. doi:
10.1017/S1368980013003546
11. Popkin BM, Adair LS, Ng SW. Global nutrition
transition and the pandemic of obesity in devel-
oping countries. Nutr Rev 2012;70:3-21.doi:
10.1111/j.1753-4887.2011.00456.x
12. Garcia G, Sunil TS, Hinojosa P. The fast food
and obesity link: consumption patterns and se-
verity of obesity. Obes Surg 2012; 22:810-818.doi:
10.1007/s11695-012-0601-8.
13. Mozaffarian D, Hao T, Rimm EB, Willett WC,
Hu FB. Changes in diet and lifestyle and long-
term weight gain in women and men. N Engl J
Med2011; 364:2392-2404.
doi: 10.1056/NEJMoa1014296
14. Duffey KJ, Gordon-Larsen P, Jacobs DR Jr,
Williams OD, Popkin BM. Differential associa-
tions of fast food and restaurant food consump-
tion with 3-y change in body mass index. The
Coronary Artery Risk Development in Young
Adults Study. Am J ClinNutr2007; 85:201208.
15. Bes-Rastrollo M, Sánchez-Villegas A, Gómez-
Gracia E, Martínez JA, Pajares RM, Martínez-
González MA. Predictors of weight gain in a
Mediterranean cohort: the Seguimiento Univer-
sidad de Navarra Study 1. Am J Clin Nutr
2006;83:362-370.
16. Jeffery RW, Baxter J, McGuire M, Linde J. Are
fast food restaurants an environmental risk fac-
tor for obesity?Int J Behav Nutr Phys Act
2006;3:2.doi: 10.1186/1479-5868-3-2
17. Whitton C, Ma Y, Bastian AC, Fen Chan M,
Chew L. Fast-food consumers in Singapore:
demographic profile, diet quality and weight sta-
tus. Public Health Nutr 2013; 17:1805-1813. doi:
10.1017/S1368980013001997
18. Anderson B, Rafferty AP, Lyon-Callo S, Fuss-
man C, Imes G. Fast-food consumption and
obesity among Michigan adults. Prev Chronic Dis
2011; 8:A71.
19. Bahadoran Z, Mirmiran P, Golzarand M, Hos-
seini-Esfahani F, Azizi F. Fast food consump-
tion in Iranian adults; dietary intake and cardio-
vascular risk factors: Tehran Lipid and Glucose
Study. Arch Iran Med 2012; 15:346-351.doi:
012156/AIM.006
20. KrugerDJ, Greenberg E, Murphy JB, Difazio
LA, Youra KR. Local concentration of fast food
outlets is associated with poor nutrition and
obesity. Am J Health Promot 2014;28:340-343.
doi: 10.4278/ajhp.111201-QUAN-437
21. French SA, Harnack L, Jeffery RW. Fast food
restaurant use among women in the Pound of
Prevention study: dietary, behavioral and demo-
graphic correlates. Int J Obes Relat Metab Disord
2000; 24:1353-1359.doi:10.1038/sj.ijo.0801429
22. Jeffery RW, French SA. Epidemic obesity in the
United States: are fast foods and television view-
ing contributing? Am J Public Health 1998;
88:277280.doi: 10.2105/ajph.88.2.277
23. Virtanen M, Kivimäki H, Ervasti J, Oksanen
T, Pentti J, Kouvonen A, et al. Fast-food outlets
and grocery stores near school and adolescents'
eating habits and overweight in Finland. Eur J
Public Health2015;25:650-655. doi: 10.1093/eu-
rpub/ckv045
24. An R, Liu J. Fast-food and full-service restau-
rant consumption in relation to daily energy and
nutrient intakes among US adult cancer survi-
vors, 2003-2012. Nutr Health 2015. pii:
0260106015594098.
doi:10.1177/02601060-15594098
Bahadoran et al.: Fast Food Pattern and Cardiometabolic Disorders
239
25. Barnes TL, French SA, Mitchell NR, Wolfson J.
Fast-food consumption, diet quality and body
weight: cross-sectional and prospective associa-
tions in a community sample of working adults.
Public Health Nutr 2015; 15:1-8.
doi: 10.1017/S1368980015001871
26. Devaraj S, Wang-Polagruto J, Polagruto J, Keen
CL, Jialal I. High-fat, energy-dense, fast-food-
style breakfast results in an increase in oxidative
stress in metabolic syndrome. Metabolism2008;
57:867-870.
doi: 10.1016/j.metabol.2008.02.016
27. Odegaard AO, Koh WP, Yuan JM, Gross MD,
Pereira MA. Western-style fast food intake and
cardiometabolic risk in an Eastern country. Cir-
culation 2012; 126:182-188.doi:
10.1161/CIRCULATIONAHA.111.084004
28. Halton TL, Willett WC, Liu S, Manson JE,
Stampfer MJ, Hu FB. Potato and French fry
consumption and risk of type 2 diabetes in
women. Am J Clin Nutr 2006; 83:284 290.
29. Krishnan S, Coogan PF, Boggs DA, Rosenberg
L, Palmer JR. Consumption of restaurant foods
and incidence of type 2 diabetes in African
American women. Am J Clin Nutr 2010; 91:465
471.doi: 10.3945/ajcn.2009.28682.
30. Babio N, Sorlí M, Bulló M, Basora J, Ibarrola-
Jurado N, Fernández-Ballart J, et al. Association
between red meat consumption and metabolic
syndrome in a Mediterranean population at high
cardiovascular risk: cross-sectional and 1-year
follow-up assessment. Nutr Metab Cardiovasc Dis
2012; 22:200-207.
doi: 10.1016/j.numecd.2010.06.011
31. Kechagias S, Ernersson A, Dahlqvist O,
Lundberg P, Lindström T, Nystrom FH. Fast-
food-based hyper-alimentation can induce rapid
and profound elevation of serum alanine ami-
notransferase in healthy subjects. Gut2008;
57:649-654.doi: 10.1136/gut.2007.131797
32. Micha R, Wallace SK, Mozaffarian D. Red and
processed meat consumption and risk of inci-
dent coronary heart disease, stroke, and diabetes
mellitus: a systematic review and meta-analysis.
Circulation 2012;121:22712283.doi:
10.1161/CIRCULATIONAHA.109.924977
33. Prentice AM, Jebb SA. Fast foods, energy den-
sity and obesity: a possible mechanistic link.
Obes Rev 2003;4:187-194.doi:10.1046/j.1467-
789x.2003.00117.x
34. Wilks DC, Mander AP, Jebb SA, Thompson
SG, Sharp SJ, Turner RM. Dietary energy den-
sity and adiposity: Employing bias adjustments
in a meta-analysis of prospective studies. BMC
Public Health2011; 11,48.doi:10.1186/1471-2458-
11-48.
35. Bowman SA, Gortmaker SL, Ebbeling CB, Pe-
reira MA, Ludwig DS. Effects of fast-food con-
sumption on energy intake and diet quality
among children in a national household survey.
Pediatrics2004; 113:112118.
doi: 10.1542/peds.113.1.112
36. Ebbeling CB, Sinclair KB, Pereira MA, Garcia-
Lago E, Feldman HA, Ludwig DS. Compensa-
tion for energy intake from last fast food among
overweight and lean adolescents. JAMA 2004;
291:28282833.
doi: 10.1001/jama.291.23.2828
37. Barrado E, Mayo MT, Tesedo A, Romero H,
Rosa Fde L. Fat composition of several "fast
food". Nutr Hosp 2008; 23:148-158.
38. Stender S, Dyerberg J, Astrup A. Fast food: un-
friendly and unhealthy. Int J Obes(Lond)
2007;31:887-890. doi: 10.1038/sj.ijo.0803616
39. Koh-Banerjee P, Chu NF, SpiegelmanD, Ros-
ner B, Colditz G, Willett W, et al. Prospective
study of the association of changes in dietary in-
take, physical activity, alcohol consumption, and
smoking with 9-y gain in waist circumference
among 16 587 US men. Am J ClinNutr2003;
78:719-727.
40. Rasmussen LB, Lassen AD, Hansen K,
Knuthsen P, Saxholt E, Fagt S. Salt content in
canteen and fast food meals in Denmark. Food
Nutr Res2010; 54. doi: 10.3402/fnr.v54i0.2100
41. Ogihara T, Asano T, Fujita T. Contribution of
salt intake to insulin resistance associated with
hypertension. Life Sci2003; 73:509-523.doi:
10.1016/S0024-3205(03)00315-1
42. Ramel A, Gudmundsdottir FD, Thorsdottir I.
Effects of two different types of fast food on
postprandial metabolism in normal and over-
weight subjects. Eur J Clin Nutr 2012; 66:1193-
1198. doi: 10.1038/ejcn.2012.125.
43. Charlton M, Krishnan A, Viker K, Sanderson S,
Cazanave S, McConico A, et al. Fast food diet
mouse: novel small animal model of NASH
with ballooning, progressive fibrosis, and high
physiological fidelity to the human condition.
Am J Physiol Gastrointest Liver Physiol 2011;
301:G825-G834. doi:
Health Promotion Perspectives, Vol. 5, No. 4, 2015; P:231-240
240
10.1152/ajpgi.00145.2011
44. El-Seweidy MM, Hashem RM, Abo-El-matty
DM, Mohamed RH. Frequent inadequate sup-
ply of micronutrients in fast food induces oxida-
tive stress and inflammation in testicular tissues
of weanling rats. J Pharm Pharmacol 2008;
60:1237-1240.doi: 10.1211/jpp.60.9.0017.
... It is generally recognized that fast food, such as sandwich, hot dog, pizza and fried potato are nutrient-poor, energy-dense and has been de ned as highly processed foods served as quick meals in snack bars and restaurants [8,9]. They are poor sources of vitamins, minerals, and dietary ber, and are high in re ned carbohydrates, sodium, and trans-fatty acids [10]. ...
Preprint
Full-text available
Background: There has been an increase in the consumption of fast food as well as overweight/obesity in recent decades. Methods: The purpose of this study was to estimate the prevalence of fast food consumption (FFC), soft drink consumption (SDC) and to evaluate its association with abdominal and general obesity. We conducted an analysis of cross-sectional study by selecting 724 students randomly from 2 largest universities in Zahedan, southeast of Iran, who were studying medical and basic sciences in 2018. Data collection through filling out an modified version of NELSON’s fast food questionnaire and measurement of anthropometric indices, such as waist-to-height ratio (WHtR), waist circumference (WC) and Body Mass Index (BMI) was conducted. Statistical analysis were conducted using chi-square, kruskal wallis tests and multivariate logistic regressions. Results: According to our results, 85.5% (83.6% of girls and 87.8% of boys) had at least one type of fast food consumed in the recent month including sandwich 46.0%, pizza 17.0%, and fried potatoe 9%. FFC was related to WHtR (OR: 3.4, 95 CI: 1.5, 8.0) as abdominal obesity and was associated to WC (p< 0.05 ) as central obesity, but was not related and associated to BMI (OR: 1.8, 95% CI: 0.9, 3.0) as general obesity. Moreover, a significant relationship was observed between obesity and SDC (OR: 1.5, 95% CI: 1.1, 2.3). Conclusion: consumption of fast foods was associated to central obesity based on WC and abdominal obesity based on WHtR, but did not associated to general obesity based on BMI. Also, consumption of soft drinks was associated to central obesity.
... Such ultra-processed foods worsen serum lipid levels, induce the release of proinflammatory molecules from adipose tissue [375] and reduce the antioxidant defenses [376], resulting in cardiometabolic risk [615][616][617]. Unfortunately, these products are affordable, highly palatable and easy to find, facilitating their prevalence in patient diets and accelerating the incidence of atherosclerotic disease in recent years [618]. ...
Article
Full-text available
Dietary risk factors play a fundamental role in the prevention and progression of atherosclerosis and PAD (Peripheral Arterial Disease). The impact of nutrition, however, defined as the process of taking in food and using it for growth, metabolism and repair, remains undefined with regard to PAD. This article describes the interplay between nutrition and the development/progression of PAD. We reviewed 688 articles, including key articles, narrative and systematic reviews, meta-analyses and clinical studies. We analyzed the interaction between nutrition and PAD predictors, and subsequently created four descriptive tables to summarize the relationship between PAD, dietary risk factors and outcomes. We comprehensively reviewed the role of well-studied diets (Mediterranean, vegetarian/vegan, low-carbohydrate ketogenic and intermittent fasting diet) and prevalent eating behaviors (emotional and binge eating, night eating and sleeping disorders, anorexia, bulimia, skipping meals, home cooking and fast/ultra-processed food consumption) on the traditional risk factors of PAD. Moreover, we analyzed the interplay between PAD and nutritional status, nutrients, dietary patterns and eating habits. Dietary patterns and eating disorders affect the development and progression of PAD, as well as its disabling complications including major adverse cardiovascular events (MACE) and major adverse limb events (MALE). Nutrition and dietary risk factor modification are important targets to reduce the risk of PAD as well as the subsequent development of MACE and MALE.
... Sebagian besar responden (41,4%) dalam penelitian ini mengaku mengurangi konsumsi fast food dan 35,4% responden mengurangi konsumsi gorengan selama masa pandemi. Perubahan ini memberikan efek yang baik bagi tubuh, mengingat beberapa penelitian sebelumnya telah mengaitkan kebiasaan konsumsi fast food dengan peningkatan berat badan dan risiko penyakit 20,21 . Penelitian di Spanyol menunjukkan hasil yang berbeda dimana sebagian besar respondennya mengaku tidak mengalami perubahan selama masa pandemi dalam hal konsumsi fast food (60%) dan makanan yang digoreng (73,4%) 10 . ...
Article
Full-text available
Latar Belakang: COVID-19, pada awalnya terdeteksi pada Desember tahun 2019 di Negara China, tepatnya di Kota Wuhan, Provinsi Hubei. Penyebaran penyakit ini terjadi secara cepat dan luas hingga ke seluruh dunia. Hingga saat ini, COVID-19 telah menjadi perhatian utama di setiap negara, termasuk Indonesia. Peraturan pemerintah untuk membatasi aktivitas atau kegiatan di luar dan himbauan untuk tetap di rumah, menyebabkan berbagai perubahan perilaku hidup masyarakat, termasuk perubahan perilaku makan. Dampak pandemi COVID-19 sangat dirasakan oleh seluruh golongan masyarakat termasuk mahasiswa, baik secara sosiologis, psikologis maupun fisiologis. Tujuan: Adapun tujuan dari penelitian ini yaitu untuk mengetahui dampak pandemi COVID-19 terhadap perubahan perilaku makan mahasiswa di Indonesia. Metode: Penelitian ini merupakan studi kuantitatif deskriptif. Data dikumpulkan secara online pada bulan April-Mei 2021 dengan menggunakan kuesioner. Jumlah sampel diperoleh sebanyak 1.185 mahasiswa yang diambil dengan metode Snowball Sampling. Hasil: Berdasarkan hasil penelitian ini, diketahui bahwa perubahan perilaku makan selama masa pandemi COVID-19 yang terjadi pada mahasiswa di Indonesia, diantaranya yaitu peningkatan frekuensi masak di rumah (52.3%), peningkatan konsumsi cemilan (47.1%), peningkatan konsumsi sayur (52.9%), penurunan konsumsi fast food (41.4%), dan penurunan kebiasaan membeli makanan/minuman/jajan di luar rumah secara langsung (41.6%). Selain itu, sebagian besar mahasiswa (34.8%) mengaku tidak pernah mengonsumsi suplemen selama masa pandemi. Kesimpulan: Disarankan kepada mahasiswa Indonesia, untuk tetap menjaga pola makan selama masa pandemi COVID-19 dengan menerapkan prinsip gizi seimbang.
... For the fast food pattern, our finding was supported by a cross-sectional study, including 2,560 Chinese participants, which showed that Western fast food patterns were not associated with hypertension (46). The fast food pattern was similar to the high fast food pattern, which was reported as a risk factor for cardiovascular disease (47), but participants with better adherence to the fast food pattern tended to be younger and had fewer sleeping disorders in our study. Younger and better sleeping quality has been considered as protective factors for BP (48,49). ...
Article
Full-text available
Objective This study aimed to explore the association between dietary patterns and hypertension based on a community–based survey in Suzhou, Eastern China. Methods This cross–sectional analysis was undertaken from the subset of the Suzhou Food Consumption and Health State Survey in 2018–2019. Adults aged ≥ 18 years were invited to participate in this survey. Dietary intake was collected by a 24–h dietary recall and a weighing method over three consecutive days (including two weekdays and one weekend day). Dietary patterns were defined using factor analysis. Association between the dietary patterns and hypertension was examined by multivariable logistic regression models with adjustment for covariates. Moreover, sensitivity analysis was used to reinforce our findings. Results A total of 2,718 participants were included in the final analysis. Rice-vegetable pattern, fast food pattern, fruit-dairy pattern, and wheat-meat pattern were identified. We observed that the fruit-dairy pattern was inversely associated with hypertension after adjustment for all the covariates (OR = 0.55; 95% CI: 0.40, 0.75; P = 0.002). The association between the wheat-meat pattern and hypertension was attenuated and became statistically nonsignificant in sensitivity analyses. The other two patterns were not significantly associated with hypertension ( P > 0.05). Conclusion The fruit-dairy pattern was inversely associated with the risk of hypertension among Chinese adults. Our findings further emphasize the important role of optimal diet combination in the prevention of hypertension.
... Food purchased outside the home contributes to increasing calorie consumption because it contains more fat, saturated fat, sugar, and added sugar compared to home-cooked food. Overweight, abdominal fat gain, and oxidative stress were caused by frequent consumption of fast foods [7]. This will undoubtedly contribute to increased body mass index (BMI), obesity, and non-communicable diseases. ...
Article
Full-text available
Technology development causes easy access to various sectors, including ordering food online. Fast food is one of the foods that many people reviewed in online applications that are high in fat with a density of 40% of total calories. Meanwhile, the consumption of vegetables and fruits of Indonesia’s people is still inadequate; only 63.3% consume as recommended. These things will undoubtedly increase the body mass index (BMI) and increase the risk of overweight and obesity. This study aims to analyze the impact of online order development on fast food, vegetables, and fruits consumption behavior on students in Surabaya. This descriptive cross-sectional study enrolled 317 students in Surabaya City, East Java, Indonesia. The online survey collected data through online platforms, SurveyMonkey. Data were analyzed in statistical software SPSS 25.0 using multivariate binomial linear regression test. The significance level was set at p<0.05. Regression analysis shows that the habit of ordering boba drinks with a weekly frequency has a significant relationship with the incidence of overweight/obesity in respondents (p = 0.015; OR = 3.037; 95% CI (1.236-7.462)) when compared to respondents who have the habit of ordering and consuming boba drinks every month. Consumption habits of boba drink are associated with higher body mass index (BMI), increasing the risk of overweight and obesity. A policy from the government and related parties is needed to regulate boba consumption limits for the community.
... Fast food which contained high energy, cholesterol, and sodium was a risk factor for overweight or obesity (Bahadoran et al., 2015). However, whether the consumption of fast food and level of activity level could affect the prevalence of overweight among adolescents during lockdown was still unknown. ...
Article
Full-text available
During the Covid-19 pandemic, the community's physical activity decreased while fast food is preferable. The imbalance in energy intake could lead to triggering an excess nutritional status. The purpose of the study was to analyze the association between fast-food consumption and physical activity on the nutritional status of students during the Covid-19 pandemic. A cross-sectional study with accidental sampling among 84 students at one of the private Universities located in East Jakarta was conducted. The data were nutritional status, fast-food consumption, and physical activity. Statistical analysis was a chi-square test. Almost one-third of students were overweight (29,8%), more than half of them had low physical activity levels (51,2%) and frequently consumed fast-food (57,2%). Both fast food consumption and physical activity were not different between students with a normal nutritional status and overweight during the Pandemic (p-value>0,05). This concluded that the trend of consuming fast food while performing low physical activity occurred not only for those with overweight but those who have normal nutritional status.
Article
Background: Metabolic syndrome is a constellation of risk factors associated with the development of cardiovascular disease and increased all-cause mortality. Data examining the prevalence of metabolic syndrome among emergency medical services (EMS) clinicians are limited. Methods: We conducted a cross-sectional study of EMS clinicians and firefighters from three fire departments with transport-capable EMS divisions. Data were collected from compulsory annual physical exams for 2021 that included age, sex, race, body mass index (BMI), waist circumference, blood pressure, cholesterol levels, and hemoglobin A1c level. These data were used to determine the prevalence of meeting metabolic syndrome criteria. We calculated descriptive statistics of demographics, anthropometrics, and metabolic syndrome criteria for EMS clinicians and firefighters. We used chi-square tests to compare the proportion of EMS clinicians and firefighters meeting criteria for the whole group and among age groups of <40 years old, 40 to 59 years old, and ≥60 years old. We used logistic regression to estimate the odds of meeting criteria in EMS clinicians compared to firefighters, adjusted for age, sex, race, and BMI. Results: We reviewed data for 65 EMS clinicians and 239 firefighters. For the combined cohort, 13.2% (40/304) were female and 95.1% (289/304) were White. The median age for EMS clinicians was 34 years versus 45 years in firefighters (p < 0.0001). Metabolic syndrome criteria were met in 27.3% (83/304) of the entire group. The prevalence of meeting criteria among EMS clinicians and firefighters was 33.9% (22/65) and 25.5% (61/239), respectively (p = 0.18). Of the participants who were younger than age 40, 36.6% (15/41) of EMS clinicians versus 9.1% (7/74) of firefighters met criteria for metabolic syndrome (p < 0.001). EMS clinicians had significantly higher odds of meeting criteria [OR 4.62 (p = 0.001)] compared to firefighters when adjusted for age, sex, race, and BMI. Conclusion: EMS clinicians had a high prevalence of metabolic syndrome at an early age, and had a higher adjusted odds of having metabolic syndrome compared to firefighters.
Preprint
Full-text available
Poor diets, including those high in fast food, are a leading cause of morbidity and mortality. Exposure to low-quality food environments, such as 'food swamps' saturated with fast food outlets (FFO), is hypothesized to negatively impact diet and related disease. However, research linking such exposure to diet and health outcomes has generated mixed findings and led to unsuccessful policy interventions. A major research limitation has been a predominant focus on static food environments around the home, such as food deserts and swamps, and sparse availability of information on mobile food environments people are exposed to and food outlets they visit as they move throughout the day. In this work, we leverage population-scale mobility data to examine peoples' visits to food outlets and FFO in and beyond their home neighborhoods and to evaluate how food choice is influenced by features of food environments people are exposed to in their daily routines vs. individual preference. Using a semi-causal framework and various natural experiments, we find that 10\% more FFO in an area increases the odds of people visiting a FFO by approximately 20\%. This strong influence of the food environment happens similarly during weekends and weekdays, is largely independent of individual income. Using our results, we investigate multiple intervention strategies to food environments to promote reduced FFO visits. We find that optimal locations for intervention are a combination of where i) the prevalence of FFO is the highest, ii) most decisions about food outlet visits are made, and most importantly, iii) visitors' food decisions are most susceptible to the environment. Multi-level interventions at the individual behavior- and food environment-level that target areas combining these features could have 1.7x to 4x larger effects than traditional interventions that alter food swamps or food deserts.
Article
Background Consuming foods-away-from-home (FAFH) is ubiquitous; yet, it is unclear how it influences diet in diverse populations. Objective The study aimed to evaluate the association between frequency and type of consumption of foods away from home (FAFH) and diet quality. Design The study had a cross-sectional design. Participants self-reported the frequency of consuming FAFH “rarely’ (≤1/week) vs. ‘frequently’ (≥2 times/week) at various commercial establishments or non-commercial FAFH (i.e., friends or relatives’ homes). Participants /Setting: Participants were adults (ages 30-75y) from the Puerto Rico Assessment of Diet, Lifestyle, and Diseases (PRADLAD) study conducted in San Juan, Puerto Rico metro area (n=239) in 2015. Main outcome measures A validated food frequency questionnaire captured dietary intake. The Alternate Healthy Eating Index-2010 (AHEI) defined diet quality. Secondary outcomes included whether participants met Dietary Guidelines for Americans (DGA) recommendations for sodium, added sugars, saturated fat, dietary fiber, total energy, and alcohol. Statistical analyses performed Linear or logistic regression models adjusted for age, sex, employment, income, education, and food insufficiency tested differences in mean AHEI scores or odds (OR: 95%CI) of meeting (vs. not meeting) intake recommendations by FAFH type and frequency. Results Overall, 54.4% and 37.2% of participants reported consuming commercial FAFH and non-commercial FAFH ‘frequently’, respectively. Consuming FAFH ‘frequently’ (vs. ‘rarely’) was associated with lower mean AHEI scores for both commercial FAFH (57.92 vs. 63.58; p=0.001), and for non-commercial FAFH (56.22 vs. 62.32: p<0.001). Consuming commercial FAFH ‘frequently’ (vs. ‘rarely’) at any type of food establishment was associated with lower odds of meeting the dietary fiber DRI (OR: 0.43; CI: 0.23, 0.81). Consuming non-commercial FAFH ‘frequently’ was associated with lower odds of meeting recommendations for sodium (OR: 0.30; CI: 0.11, 0.79) and added sugars (OR: 0.41; CI: 0.18, 0.93). Conclusions Frequent consumption of FAFH is associated with lower diet quality and lower adherence to dietary recommendations in Puerto Rico. Future studies should explore if diet quality can be improved by prioritizing healthy at-home meals and reformulating the quality of commercial FAFH.
Article
Full-text available
Away-from-home food consumption has rapidly increased, though little is known about the independent associations of restaurant food and fast food intake with body mass index (BMI) and BMI change. The aim was to compare the associations of restaurant food and fast food consumption with current and 3-y changes in BMI. Multivariate linear regression models, with control for demographic and lifestyle factors, were used to examine cross-sectional and longitudinal associations of away-from-home eating with BMI by using data from subjects of the Coronary Artery Risk Development in Young Adults Study (n = 3394) obtained at exam years 7 (1992-1993) and 10 (1995-1996). Forty percent of the sample increased their weekly consumption of restaurant or fast food, though mean (+/-SD) changes were -0.16 +/- 2.39 times/wk (P = 0.0001) and -0.56 +/- 3.04 times/wk (P < 0.0001), respectively. Cross-sectionally, fast food, but not restaurant food, consumption was positively associated with BMI. Similarly, higher consumption of fast food at year 7 was associated with a 0.16-unit higher BMI at year 10. After adjustment for baseline away-from-home eating, increased consumption of fast food only (beta: 0.20; 95% CI: 0.01, 0.39) and of both restaurant food and fast food (beta: 0.29; 95% CI: 0.06, 0.51) were positively associated with BMI change, though the estimates were not significantly different (P = 0.47). Increased consumption of restaurant food only was unrelated to BMI change (beta: -0.01; 95% CI: -0.21, 0.19), which differed significantly (P = 0.014) from the estimate for an increase in both restaurant food and fast food intake. We found differential effects of restaurant food and fast food intakes on BMI, although the observed differences were not always statistically significant. More research is needed to determine whether the differential effects are related to consumer characteristics or the food itself.
Article
Full-text available
Fast food has become a prominent feature of the diet of children in the United States and, increasingly, throughout the world. However, few studies have examined the effects of fast-food consumption on any nutrition or health-related outcome. The aim of this study was to test the hypothesis that fast-food consumption adversely affects dietary factors linked to obesity risk. This study included 6212 children and adolescents 4 to 19 years old in the United States participating in the nationally representative Continuing Survey of Food Intake by Individuals conducted from 1994 to 1996 and the Supplemental Children's Survey conducted in 1998. We examined the associations between fast-food consumption and measures of dietary quality using between-subject comparisons involving the whole cohort and within-subject comparisons involving 2080 individuals who ate fast food on one but not both survey days. On a typical day, 30.3% of the total sample reported consuming fast food. Fast-food consumption was highly prevalent in both genders, all racial/ethnic groups, and all regions of the country. Controlling for socioeconomic and demographic variables, increased fast-food consumption was independently associated with male gender, older age, higher household incomes, non-Hispanic black race/ethnicity, and residing in the South. Children who ate fast food, compared with those who did not, consumed more total energy (187 kcal; 95% confidence interval [CI]: 109-265), more energy per gram of food (0.29 kcal/g; 95% CI: 0.25-0.33), more total fat (9 g; 95% CI: 5.0-13.0), more total carbohydrate (24 g; 95% CI: 12.6-35.4), more added sugars (26 g; 95% CI: 18.2-34.6), more sugar-sweetened beverages (228 g; 95% CI: 184-272), less fiber (-1.1 g; 95% CI: -1.8 to -0.4), less milk (-65 g; 95% CI: -95 to -30), and fewer fruits and nonstarchy vegetables (-45 g; 95% CI: -58.6 to -31.4). Very similar results were observed by using within-subject analyses in which subjects served as their own controls: that is, children ate more total energy and had poorer diet quality on days with, compared with without, fast food. Consumption of fast food among children in the United States seems to have an adverse effect on dietary quality in ways that plausibly could increase risk for obesity.
Article
Full-text available
To examine the association between fast-food consumption, diet quality and body weight in a community sample of working adults. Cross-sectional and prospective analysis of anthropometric, survey and dietary data from adults recruited to participate in a worksite nutrition intervention. Participants self-reported frequency of fast-food consumption per week. Nutrient intakes and diet quality, using the Healthy Eating Index-2010 (HEI-2010), were computed from dietary recalls collected at baseline and 6 months. Metropolitan medical complex, Minneapolis, MN, USA. Two hundred adults, aged 18-60 years. Cross-sectionally, fast-food consumption was significantly associated with higher daily total energy intake (β=72·5, P=0·005), empty calories (β=0·40, P=0·006) and BMI (β=0·73, P=0·011), and lower HEI-2010 score (β=-1·23, P=0·012), total vegetables (β=-0·14, P=0·004), whole grains (β=-0·39, P=0·005), fibre (β=-0·83, P=0·002), Mg (β=-6·99, P=0·019) and K (β=-57·5, P=0·016). Over 6 months, change in fast-food consumption was not significantly associated with changes in energy intake or BMI, but was significantly inversely associated with total intake of vegetables (β=-0·14, P=0·034). Frequency of fast-food consumption was significantly associated with higher energy intake and poorer diet quality cross-sectionally. Six-month change in fast-food intake was small, and not significantly associated with overall diet quality or BMI.
Article
Full-text available
Background: There are growing concern globally regarding fast food consumption and its related cardiometabolic outcomes. In this study we investigated whether fast food consumption could affect the occurrence of metabolic syndrome (MetS) after 3-years of follow-up in adults. Methods: This longitudinal study was conducted in the framework of Tehran Lipid and Glucose Study on 1476 adults, aged 19-70 y. The usual intakes of participants were measured using a validated semi-quantitative food frequency questionnaire at baseline. Biochemical and anthropometric measurements were assessed at baseline (2006-2008) and 3 years later (2009-2011). Multiple logistic regression models were used to estimate the occurrence of the MetS in each quartile of fast food consumption. Results: The mean age of participants was 37.8±12.3 y, and mean BMI was 26.0±4.5 kg/m(2) at baseline. Participants in the highest quartile of fast food consumption were younger (33.7 vs 43.4 years, P<0.01). Higher consumption of fast food was accompanied with more increase in serum triglyceride levels and triglyceride to HDL-C ratio after the 3-year follow-up. After adjustment for all potential confounding variables, the risk of metabolic syndrome, in the highest quartile of fast foods compared with the lowest, was 1.85 (95% CI=1.17-2.95). The effects of fast food consumption on the occurrence of MetS were more pronounced in younger adults (<30 years), and participants who had greater wait to hip ratio, consumed less phytochemical-rich foods or had low-fiber diet (P<0.05). Conclusion: We demonstrated that higher consumption of fast foods had undesirable effects on metabolic syndrome after 3-years of follow-up in Iranian adults.
Article
Full-text available
Purpose: We investigated the relationship of the local availability of fast-food restaurant locations with diet and obesity. Design: We geocoded addresses of survey respondents and fast-food restaurant locations to assess the association between the local concentration of fast-food outlets, BMI, and fruit and vegetable consumption. Setting: The survey was conducted in Genesee County, Michigan. Subjects: There were 1345 individuals included in this analysis, and the response rate was 25%. Measures: The Speak to Your Health! Community Survey included fruit and vegetable consumption items from the Behavioral Risk Factor Surveillance System, height, weight, and demographics. We used ArcGIS to map fast-food outlets and survey respondents. Analysis: Stepwise linear regressions identified unique predictors of body mass index (BMI) and fruit and vegetable consumption. Results: Survey respondents had 8 ± 7 fast-food outlets within 2 miles of their home. Individuals living in close proximity to fast-food restaurants had higher BMIs t(1342) = 3.21, p < .001, and lower fruit and vegetable consumption, t(1342) = 2.67, p = .008. Conclusion: Individuals may be at greater risk for adverse consequences of poor nutrition because of the patterns in local food availability, which may constrain the success of nutrition promotion efforts. Efforts to decrease the local availability of unhealthy foods as well as programs to help consumers identify strategies for obtaining healthy meals at fast-food outlets may improve health outcomes.
Article
Introduction: Consumption of meals eaten away from home, especially from fast-food restaurants, has increased in the United States since the 1970s. The main objective of this study was to examine the frequency and characteristics of fast-food consumption among adults in Michigan and obesity prevalence. Methods: We analyzed data from 12 questions about fast-food consumption that were included on the 2005 Michigan Behavioral Risk Factor Survey, a population-based telephone survey of Michigan adults, using univariate and bivariate analyses and multivariate logistic regression, and compared these data with data on Michigan obesity prevalence. Results: Approximately 80% of Michigan adults went to fast-food restaurants at least once per month and 28% went regularly (≥2 times/wk). Regular fast-food consumption was higher among younger adults (mostly men) but was not significantly associated with household income, education, race, or urbanicity (in a multivariate framework). The prevalence of obesity increased consistently with frequenting fast-food restaurants, from 24% of those going less than once a week to 33% of those going 3 or more times per week. The predominant reason for choosing fast food was convenience. Although hypothetically 68% of adults who go to fast-food restaurants would choose healthier fast-food items when available, only 16% said they ever use nutritional information when ordering. Conclusion: The prevalence of fast-food consumption is high in Michigan across education, income, and racial groups and is strongly associated with obesity. Making nutritional information at fast-food restaurants more readily available and easier to use may help consumers to order more healthful or lower-calorie items.
Article
Healthy diet is an essential component in cancer survivorship care planning. Cancer survivors should be particularly prudent regarding their daily food choices, with an aim of ensuring safe consumption, reducing risk of recurrence or other comorbidity, and improving quality of life. We aimed to examine the impacts of fast-food and full-service restaurant consumption on daily energy and nutrient intakes among US adult cancer survivors. Nationally representative data of 1308 adult cancer survivors came from the National Health and Nutrition Examination Survey 2003-2012 waves. First-difference estimator was adopted to address confounding bias from time-invariant unobservables like personal food/beverage preferences by using within-individual variations in diet and restaurant consumption status between two non-consecutive 24-hour dietary recalls. Fast-food and full-service restaurant consumption, respectively, was associated with an increase in daily total energy intake by 125.97 and 152.26 kcal and sodium intake by 312.47 and 373.75 mg. Fast-food consumption was significantly associated with a decrease in daily vitamin A intake by 119.88 µg and vitamin K intake by 30.48 µg, whereas full-service restaurant consumption was associated with an increase in daily fat intake by 8.99 g and omega-6 fatty acid intake by 3.85 g, and a decrease in vitamin D intake by 0.93 µg. Compared with fast-food and full-service restaurant consumption at home, consumption away from home led to further reduced diet quality. Individualized nutrition counseling and food assistance programs should address cancer survivors' overall dining-out behavior rather than fast-food consumption alone. © The Author(s) 2015.
Article
Environmental factors may affect adolescents' eating habits and thereby body weight. However, the contribution of school neighbourhood environment is poorly understood. This study examined the association between proximity of a fast-food outlet or grocery store to school and adolescents' eating habits and overweight. Participants were 23 182 adolescents (mean age 15 years) who responded to a classroom survey in 181 lower secondary schools in Finland (2008-09). School location was linked to data on distance from school to the nearest fast-food outlet or grocery store (≤100 m, 101-500 m, >500 m) using global positioning system-coordinate databases. Outcomes were irregular eating habits (skipping breakfast, skipping free school lunch, skipping free school-provided snacks and not having family dinners), the accumulation of these habits and overweight, including obesity (body mass index ≥ 25 kg/m(2)). Thirteen percentage of the participants were overweight. Having a fast-food outlet or grocery store near school was associated with skipping often breakfast and free school lunch, and the accumulation of irregular eating habits. The proximity of a fast-food outlet or grocery store was associated with a 1.25-fold (95% confidence interval 1.03-1.52) risk of overweight among adolescent with a low socioeconomic status but not among those with higher socioeconomic status. This association was partly (12%) explained by the accumulation of irregular eating habits. Among adolescents from low socioeconomic background, the presence of fast-food retailers near schools is associated with accumulation of irregular eating habits and greater overweight. These findings suggest that obesogenic school neighbourhoods may contribute to social inequalities in overweight. © The Author 2015. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.
Article
Fast-food restaurants (FFR) are prevalent. Binge eating is common among overweight and obese women. For women prone to binge eating, neighbourhood FFR availability (i.e. the neighbourhood around one's home) may promote poor diet and overweight/obesity. The present study tested the effects of binge eating and neighbourhood FFR availability on diet (fat and total energy intake) and BMI among African American and Hispanic/Latino women. All measures represent baseline data from the Health is Power randomized clinical trial. The numbers of FFR in participants' neighbourhoods were counted and dichotomized (0 or ≥1 neighbourhood FFR). Participants completed measures of binge eating status and diet. Weight and height were measured and BMI calculated. 2 (binge eating status) × 2 (neighbourhood FFR availability) ANCOVA tested effects on diet and BMI while controlling for demographics. Houston and Austin, TX, USA. African American and Hispanic/Latino women aged 25-60 years. Of the total sample (n 162), 48 % had 1-15 neighbourhood FFR and 29 % were binge eaters. There was an interaction effect on BMI (P = 0·05). Binge eaters with ≥1 neighbourhood FFR had higher BMI than non-binge eaters or binge eaters with no neighbourhood FFR. There were no significant interactions or neighbourhood FFR main effects on total energy or fat intake (P > 0·05). A main effect of binge eating showed that binge eaters consumed more total energy (P = 0·005) and fat (P = 0·005) than non-binge eaters. Binge eaters represented a substantial proportion of this predominantly overweight and obese sample of African American and Hispanic/Latino women. The association between neighbourhood FFR availability and weight status is complicated by binge eating status, which is related to diet.