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Instant noodle consumption is associated with cardiometabolic risk factors among college students in Seoul

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Abstract

BACKGROUND/OBJECTIVES Increased consumption of instant noodles has recently been reported to be positively associated with obesity and cardiometabolic syndrome in South Korea, which has the highest per capita instant noodle consumption worldwide. This study aimed to investigate the association between instant noodle consumption and cardiometabolic risk factors among college students in Seoul. SUBJECTS/METHODS The study subjects consisted of 3,397 college students (1,782 male; 1,615 female) aged 18-29 years who participated in a health checkup. Information on instant noodle consumption was obtained from the participants' answers to a question about their average frequency of instant noodle intake over the 1 year period prior to the survey. RESULTS Statistical analysis using a general linear model that adjusted for age, body mass index, gender, family income, health-related behaviors, and other dietary factors important for cardiometabolic risk, showed a positive association between the frequency of instant noodle consumption and plasma triglyceride levels, diastolic blood pressure, and fasting blood glucose levels in all subjects. Compared to the group with the lowest frequency of instant noodle intake (≤ 1/month), the odds ratio for hypertriglyceridemia in the group with an intake of ≥ 3/week was 2.639 [95% confidence interval (CI), 1.393–5.000] for all subjects, while it was 2.149 (95% CI, 1.045–4.419) and 5.992 (95% CI, 1.859–21.824) for male and female students, respectively. In female students, diastolic blood pressure was also higher among more frequent consumers of instant noodles. CONCLUSIONS Our results suggest that frequent consumption of instant noodles may be associated with increased cardiometabolic risk factors among apparently healthy college students aged 18–29 years.
Nutrition Research and Practice 2017;11(3):232-239
2017 The Korean Nutrition Society and the Korean Society of Community Nutrition
http://e-nrp.org
Instant noodle consumption is associated with cardiometabolic risk
factors among college students in Seoul
In Sil Huh1*, Hyesook Kim2*, Hee Kyung Jo3, Chun Soo Lim3, Jong Seung Kim3, Soo Jin Kim4, Oran Kwon2, Bumjo Oh and
Namsoo Chang
1Seoul National University Medical Research Center, Seoul 03080, Korea
2Department of Nutritional Science and Food Management, Ewha Womans University, 52, Ewhayeodae-gil, Seodaemun-gu, Seoul 03760, Korea
3Seoul National University Health Service Center, Seoul 08826, Korea
4Health Promotion Center, Chung-Ang University Hospital, Seoul 06973, Korea
5Department of Family Medicine, SMG - SNU Boramae Medical Center, 20, Boramae-ro 5-gil, Dongjak-gu, Seoul 07061, Korea
BACKGROUND/ OBJECTIVES: Increased consumption of instant noodles has recently been reported to be positively associated
with obesity and cardiometabolic syndrome in South Korea, which has the highest per capita instant noodle consumption
worldwide. This study aimed to investigate the association between instant noodle consumption and cardiometabolic risk factors
among college students in Seoul.
SUBJECTS/METHODS: The study subjects consisted of 3,397 college students (1,782 male; 1,615 female) aged 18-29 years who
participated in a health checkup. Information on instant noodle consumption was obtained from the participants’ answers
to a question about their average frequency of instant noodle intake over the 1 year period prior to the survey.
RESULTS: Statistical analysis using a general linear model that adjusted for age, body mass index, gender, family income, health-related
behaviors, and other dietary factors important for cardiometabolic risk, showed a positive association between the frequency
of instant noodle consumption and plasma triglyceride levels, diastolic blood pressure, and fasting blood glucose levels in
all subjects. Compared to the group with the lowest frequency of instant noodle intake (1/month), the odds ratio for
hypertriglyceridemia in the group with an intake of 3/week was 2.639 [95% confidence interval (CI), 1.393-5.000] for all
subjects, while it was 2.149 (95% CI, 1.045-4.419) and 5.992 (95% CI, 1.859-21.824) for male and female students, respectively.
In female students, diastolic blood pressure was also higher among more frequent consumers of instant noodles.
CONC LUSIONS: Our results suggest that frequent consumption of instant noodles may be associated with increased cardiometabolic
risk factors among apparently healthy college students aged 18-29 years.
Nutrition Research and Practice 2017;11(3):232-239; https://doi.org/10.4162/nrp.2017.11.3.232; pISSN 1976-1457 eISSN 2005-6168
Keywords: Overweight, blood pressure, hypertriglyceridemia, metabolic factors
INTRODUCTION8)
Overconsumption of instant noodles has recently received
special attention, owing to its association with obesity and
cardiometabolic syndrome among adults in South Korea [1]. The
high-calorie content and the high concentration of refined
carbohydrates, fats, and sodium [2] in instant noodles, contribute
to an increased risk of metabolic disease [1]. Consumption of
instant noodles as a staple food source is rising in many Asian
countries [3] but South Korea is ranked the world’s number one
per capita in instant noodle consumption (72.8 servings of
instant noodles per annum) [4]. A recent survey [5] reported
that college students consume instant noodles more frequently
than adults in other age groups because of the convenience
of preparing instant noodles on school premises.
The fact that college students with unhealthy dietary habits
frequently eat instant noodles and may be at increased risk of
negative health outcomes should receive special attention
because of a recent survey that reported an increasing trend
of early premature cardiovascular diseases (CVD) death among
adults as young as 20-49 years of age in Korea [6]. There is
also an increasing trend in the proportion of individuals in the
same group of young adults with increased cardiometabolic risk
factors, such as overweight or obesity, hypertension, and elevated
blood levels of glucose and lipids [7].
Many cardiometabolic risk factors are known to be modified
by lifestyle behaviors including diet. Among many diet-related
behaviors, avoiding instant foods and/or fast food and increasing
This work was supported by the Second Stage of Brain Korea 21 Plus.
§Corresponding Authors: Namsoo Chang, Tel. 82-2-3277-3468, Fax. 82-2-3277-2862, Email. nschang@ewha.ac.kr
Bumjo Oh, Tel. 82-2-870-2682, Fax. 82-2-831-0714, Email. bumjo.oh@gmail.com
Received: February 28, 2017, Revised: April 28, 2017, Accepted: May 1, 2017
*These authors contributed to this article equally.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/)
which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
In Sil Huh et al.
233
the intake of basic and unprocessed foods, is considered a
simple but pivotal strategy. Cultivation of healthy lifestyle behaviors
including good dietary practices among young adults, such as
college students, is crucial for health promotion and disease
prevention on both an individual and national level. Among
young adults, modification of undesirable dietary habits and
a reduction in CVD risk factors, is becoming more important
for the prevention of CVD.
Recent studies that report a positive relationship between
instant noodles and obesity and cardiometabolic syndrome among
Korean adults [1,8], have focused on the general population,
including all adult age groups. Despite an increasing trend in
the proportion of young Korean adults in their 20s and 30s,
with elevated metabolic markers, no study, to our knowledge,
has previously investigated this association, by specifically
targeting young adults, such as college students [9], which are
known to be the most frequent consumers of instant noodles.
Therefore, the current study was conducted to investigate the
association between instant noodle consumption and cardio-
metabolic risk factors among young college students in Korea.
SUBJECTS AND METHODS
Study subjects
A student health checkup was conducted at the health center
of a university located in Seoul, Korea. A total of 3,481 students,
aged 18-29 years, participated in the health checkup program
from 24/04/2013-16/05/2013. Of the 3,481 subjects, 81 students
who did not respond to a food questionnaire were excluded
from the analysis. Three other students were excluded because
they were receiving treatment for chronic disorders such as
hypertension, dyslipidemia, or diabetes. In total, 3,397 subjects
(1,782 male; 1,615 female) were included in the analysis. The
study protocol was approved by the 2012 Seoul National Bioethics
Committee and the 2013 Institutional Review Board of Seoul
National University College of Medicine/Seoul National University
Hospital (No. C-1304-062-481). All individuals provided informed
consent to participate in the study.
General characteristics and instant noodle consumption survey
All of the students completed an online survey that ascertained
demographic and socioeconomic factors, and health-related
behaviors including age, height, weight, family income, alcohol
consumption, smoking behavior, and physical activity. Family
monthly income was classified into < $2000 USD, $2000-4000
USD, and > $4000 USD. Alcohol consumption was categorized
as non-drinker, moderate drinker [weekly alcohol consumption
< 14 drinks (males) or < 7 drinks (females), where 1 drink consti-
tutes 14 g pure alcohol], and heavy drinker [weekly alcohol
consumption > 14 drinks (males) or > 7 drinks (females)]. Smoking
behavior was classified as non-smokers, ex-smokers, or current
smokers, depending on current smoking status. Physical activity
was classified as highly active (1500 MET-min/week, for any
strenuous physical activity practiced > 3 d/week or 3000
MET-min/week, for any activity conducted daily), moderately
active (intense physical activity for > 20 min/week or moderate
activity or walking 5 d/week for > 30 min/d), or no physical
activity/inactive (below a moderate level of physical activity).
Information on instant noodle consumption was obtained
from the participants’ answers to a question about their average
frequency of instant noodle intake over the 1 year period prior
to the survey. The questionnaire listed several potential candidate
foods important for cardiometabolic risk in addition to instant
noodles (fruits [1,10], vegetables [1,10], milk and dairy products
[11], high-fat fish [1,12], high-fat and processed meats [1,13],
sweets and confectionery [1,14], and carbonated beverages
[1,15]), which was divided into nine frequency categories: barely
eat, once/month, 2-3 times/month, 1-2 times/week, 3-4 times/
week, 5-6 times/week, once/day, twice/day, and 3 times/day.
Those food groups were fruits, vegetables (except Kimchi), milk
and dairy products (yogurt/cheese, etc.), high-fat fish (mackerel/
sardines/tuna/herring/salmon, etc.), high-fat and processed
meats (fresh bacon/beef ribs/charcoal grilled meat/ tripe/ham/
sausage/bacon), instant noodle/cup noodle, sweets and confec-
tionery (cakes/cookie/pies/candies/chocolates), and carbonated
beverages (coke/sprite/soft drinks/fruit-flavored drinks except
100% fruit juice). In this study, the consumption of these foods
as well as instant noodle was divided into 4 categories (1
time/month, 2-3 times/month, 1-2 times/week, and 3 times/
week) according to frequency distribution.
Anthropometric and clinical examination
Anthropometric measurements were taken by a trained nurse.
Standing height was measured to the nearest 0.1 cm with a
stadiometer (BSM 330, Biospace Co. Seoul, South Korea). Body
weight was measured to the nearest 0.1 kg using an Inbody
520 (Biospace Co., Ltd., Seoul, Korea). Body mass index (BMI)
was calculated as weight (kg) divided by the square of the
height (m2). Waist circumference was measured at the midpoint
between the top of the iliac crest and the lowest rib, without
any garments on. Blood pressure was taken when participants
had been at rest for > 5 min, using an automatic blood pressure
measurement system (CK-301, Spirit Medical Co., Taiwan). The
second measured value was recorded for above-normal range
blood pressure. When two preceding measurements were within
the normal range, another measurement was conducted manually.
Blood samples were drawn after a minimum 12-h overnight fast,
collected in EDTA-containing tubes, and centrifuged at 3,000
rpm, at 4°C, for 20 min (Hanil Science Industrial Co., Ltd., Seoul,
Korea). Fasting plasma levels of glucose, triglycerides, total
cholesterol, and high density lipoprotein (HDL) cholesterol were
assessed with an autoanalyzer (Cobas 6000, Roche Diagnostics
International Ltd., Rotkreuz, Switzerland). Low density lipoprotein
(LDL) cholesterol levels were calculated using the following
equation, proposed by Friedwald [16] and Lauer [17]:
LDL-cholesterol = total cholesterol - HDL-cholesterol -
(triglycerides/5)
Definition of metabolic syndrome
Metabolic syndrome was diagnosed based on the Adult
Treatment Panel III of the National Cholesterol Education
Program’s (NCEP ATP III) standard diagnostic criteria [18]. Central
obesity was defined as an absolute waist circumference > 90
cm (males) or > 85 cm (females), based on the guidelines of
the Korean Society for the Study of Obesity [19]. The criteria
for metabolic syndrome were as follows: (1) abdominal obesity:
234
Instant noodle and cardiometabolic risk factors
Total (N = 3,397) Male (N = 1,782) Female (N = 1,615)
1
time/month
(N = 937)
2-3
times /mon th
(N = 1,012)
1-2
times/week
(N = 1,050)
3
times/week
(N = 398)
P-value2)
1
time/month
(N = 365)
2-3
times/ month
(N = 478)
1-2
times/week
(N = 657)
3
times/week
(N = 282)
P-value2)
1
time/month
(N = 572)
2-3
times/month
(N = 534)
1-2
times/week
(N = 393)
3
times/week
(N = 116)
P-value2)
Age (yrs) 22.3 ± 2.8 22.3 ± 2.9 22.4 ± 2.9 22.6 ± 3.0 0.3640 22.6 ± 2.9 22.7 ± 3.1 22.6 ± 3.1 22.6 ± 3.0 0.9814 22.2 ± 2.7 21.9 ± 2.7 22.1 ± 2.7 22.4 ± 3.0 0.2674
BMI (kg/m2) 21.2 ± 2.6 21.3 ± 2.6 21.8 ± 2.8 21.9 ± 3.1 < 0.0001 22.5 ± 2.7 22.5 ± 2.7 22.8 ± 2.7 22.7 ± 3.1 0.3232 20.4 ± 2.1 20.2 ± 2.1 20.3 ± 2.1 20.2 ± 2.2 0. 5145
Sex < 0.0001
Male 365 (39.0) 478 (47.2) 657 (62. 6) 282 (70. 9)
Female 572 (61.0) 534 (52.8) 393 (37. 4) 116 (29. 1)
Family income 0.0061 0.0371 0.5646
< 2000 US$/mo 102 (10.9) 100 (9.9) 79 (7.5) 56 (14.1) 45 (12.3) 50 (10.5) 54 (8.2) 44 (15. 6) 57 (10.0) 50 (9.4) 25 (6.4) 12 (10.3)
2000-4000 US$/mo 281 (30. 0) 3 11 (30.7 ) 349 (33.2) 130 (32. 7) 124 (34.0) 158 (33. 1) 229 (34.9) 9 8 (34.8) 1 57 (27.5) 153 (28. 7) 120 (30.5) 32 ( 27.6)
> 4000 US$/mo 554 (59.1) 601 (59.4) 622 (59.2) 212 (53. 3) 196 (53.7) 270 (56. 5) 374 (56.9) 140 (49.7) 358 (62.6) 331 (62.0) 2 48 (63.1) 72 (62.1)
Alcohol consumption < 0.0001 < 0.000 1 < 0.000 1
Non-drinker 122 (13.7) 75 (7.9) 61 (6.1) 27 (7.2) 42 (12.2) 30 (6.7) 35 ( 5.5) 16 (6.0) 80 (14. 7) 45 (9.0) 26 (7.1) 11 (10.2)
Moderate drinker 695 (78.0) 752 (79. 4) 782 (7 8.3) 266 ( 71.3) 276 (80.0) 366 ( 81.5) 507 (79.8) 191 (72.1) 419 (76.7) 386 (77.5) 275 (75.6) 75 (69.4)
Heavy drinker 74 (8.3) 120 (12.7) 156 (15.6) 80 (21. 5) 27 (7.8) 53 (11.8) 93 (14.7) 58 ( 21.9) 47 (8.6) 67 (13.5) 63 (17.3) 2 2 (20.4)
Smoking behavior < 0.0 001 0.0018 0.1060
Non-smoker 867 (93.8) 901 (90.5) 900 (87. 4) 324 (82. 0) 313 (87.9) 391 (83. 4) 541 (83.4) 218 (77.6) 554 (97.5) 510 (96.8) 359 (94.2) 106 (93.0)
Ex-smoker 28 (3.0) 49 (4.9) 61 (5.9) 23 (5.8) 21 (5. 9) 40 (8.5) 50 (7.7) 19 (6. 8) 7 (1.2) 9 (1.7) 11 (2.9) 4 (3.5)
Current smoker 29 (3. 1) 46 (4.6) 69 (6.7) 48 (12.2) 22 (6.2) 38 (8.1) 58 (8. 9) 44 (15.7) 7 (1.2) 8 (1.5) 11 (2.9) 4 (3.5)
Physical activity 0.0127 0.2366 0.0008
Low 87 (9.6) 67 (6.8) 98 (9.7) 39 (10.0) 46 (13.1) 41 (8.9) 83 (1 3.0) 34 (12.4) 41 ( 7.3) 26 (5.0) 15 (4.0) 5 (4.4)
Moderate 592 (65.0) 623 (63.4) 605 (59.8) 225 (57.8) 224 (63.6) 304 (65. 9) 394 (61.9) 162 (58.9) 368 (65.8) 319 (61.2) 211 (56.3) 63 (55.3)
High 232 (25.5) 292 (29.7) 309 (3 0.5) 125 ( 32.1) 82 (23.3) 116 (25.2) 160 (25.1) 79 (28.7) 150 (26.8) 176 (33.8) 149 (39.7) 46 (40.4)
BMI: body mass index
1) Data are presented as mean±SD or N(%). Alcohol consumption, smoking behav ior, and physical activity data were anal yzed in 3,210, 3,345, and 3,294 subjects, respectively .
2)
P
-value by one-way analysis of var iance or χ2 test.
Table 1. Characteristics of study participants according to the frequency of instant noodle consumption1)
waist circumference > 90 cm (males) or > 85 cm (females), (2)
high blood pressure: systolic blood pressure 130 mmHg or
diastolic blood pressure 85 mmHg, (3) impaired fasting
glucose: fasting blood sugar 100 mg/dL, (4) high triglycerides:
triglycerides 150 mg/dL, and (5) low HDL- cholesterol: < 40
mg/dL (males) or < 50 mg/dL (females). Subjects who met three
or more of these criteria, were diagnosed with metabolic
syndrome.
Statistical analysis
Data were expressed as the mean and standard deviations
(SD) or as percentages (categorical), where appropriate. Differences
in sociodemographic and behavioral characteristics among the
instant noodle intake groups were analyzed using the Chi-square
(χ2) test. General characteristics, such as age and BMI, were
compared by one-way analysis of variance (ANOVA). The χ2 test
was applied to determine differences in the distribution of the
number of metabolic syndrome components, according to instant
noodle consumption. Potential confounders in this study included
age, BMI, gender, family income (< $2000 USD/month, $2000-
4000 USD/month, > $4000 USD/month), alcohol consumption
(non-drinker, moderate drinker, heavy drinker), smoking behavior
(non-smoker, ex-smoker, current smoker), physical activity (low,
moderate, high), and consumption frequency of fruits, vegetables,
milk and dairy products, high-fat fish, high-fat and processed
meats, sweets and confectionery and carbonated beverages (1
time/month, 2-3 times/month, 1-2 times/week, 3 times/week).
After adjusting for these confounders, a general linear model
(GLM) was constructed to examine the differences in the
metabolic parameters among the instant noodle consumption
groups. Multiple logistic regression analysis was also performed
to estimate the odds ratios (ORs) and 95% confidence intervals
(CIs) for the cardiometabolic risk factors depending on instant
noodle consumption. While performing the GLM or multiple
logistic regression analyses, subjects with missing data for
alcohol consumption (N = 187), smoking behavior (N = 52), and
physical activity (N = 103) were excluded. All statistical analyses
were performed using SAS 9.4 (SAS Inc., Cary, NC, USA). The
significance level was set at P<0.05.
RESULTS
Characteristics of study participants according to the frequency
of instant noodle consumption
The mean age of all subjects was 22.4 ± 2.9 years, and did
not differ among the instant noodle intake groups. Males were
more likely to frequently consume instant noodles (3 times/
week) than females. Subjects who frequently consumed instant
noodles, had a lower family income level than infrequent
consumers. Frequent consumers of instant noodles, drank more
alcohol, were more likely to be current smokers, and were more
physically active (Table 1). Frequent consumers of instant
noodles also frequently consumed high-fat fish, high-fat and
processed meats, sweets and confectionery, and carbonated
beverages, and had less frequent consumption of fruits and
vegetables (Table 2).
Metabolic parameters according to the frequency of instant
noodle consumption
For all subjects, plasma triglyceride levels (P= 0.0016), diastolic
In Sil Huh et al.
235
Total (N = 3,397) Male (N = 1,782) Female (N = 1,615)
1
time/month
(N = 937)
2-3
times/ month
(N = 1,012)
1-2
times/week
(N = 1,050)
3
times/week
(N = 398)
P-value2)
1
time/month
(N = 365)
2-3
times/ month
(N = 478)
1-2
times/week
(N = 657)
3
times/week
(N = 282)
P-value2)
1
time/month
(N = 572)
2-3
times/ month
(N = 534)
1-2
times/week
(N = 393)
3
times/week
(N = 116)
P-value2)
Fruits < 0.0001 < 0.0001 0.0257
1 time/month 89 (9.5) 58 (5.7) 76 (7.2) 55 ( 13.8) 56 (15.3) 34 (7.1) 57 (8.7) 49 (17.4) 33 (5.8) 24 (4.5) 19 (4.8) 6 (5.2)
2-3 times/month 110 (11.7) 149 (14.7) 185 (17.6) 74 (18.6) 45 (12.3) 81 (16.9) 129 (19.6) 48 (17.0) 65 (11.4) 68 (12.7) 56 (14.2) 26 (22.4)
1-2 times/week 213 (22.7) 286 (28.3) 316 (30.1) 109 (27.4) 91 (24.9) 152 (31.8) 209 (31.8) 79 (28.0) 122 (21.3) 134 (25.1) 107 (27.2) 30 (25.9)
3 times/week 525 (56.0) 519 (51. 3) 473 (45.1) 160 (40.2) 173 (47.4 ) 211 ( 44.1) 262 (39.9) 106 (37.6) 352 (61.5) 308 (57.7) 211 (53.7) 54 (46.5)
Vegetables (except Kimchi) 0.0335 0.1276 0.0528
1 time/month 32 (3.4) 26 (2.6) 28 (2.7) 24 ( 6.0) 19 (5.2) 12 (2. 5) 20 (3 .0) 17 (6.0) 13 (2.3) 14 (2.6) 8 (2.0) 7 (6. 0)
2-3 times/month 42 (4.5) 54 (5.3) 53 (5.0) 22 (5.5) 20 (5.5) 32 (6.7) 28 (4.3) 15 (5.3) 22 (3.9) 22 (4.1) 25 (6.4) 7 (6.0)
1-2 times/week 161 (17.2) 190 (18.8) 210 (20.0) 83 (20.9) 76 (20.8) 88 (18.4) 133 (20.2) 60 (21.3) 85 (14.9) 102 (19.1) 77 (19.6) 23 (19.8)
3 times/week 702 (74.9) 742 (73. 3) 759 (72.3) 269 (67.6) 250 (68.5 ) 346 ( 72.4) 476 (72.5) 190 (67.4) 452 (79.0) 396 (74.2) 283 (72.0) 79 (68.1)
Milk and dairy products 0.2142 0.0840 0.4652
1 time/month 57 (6.1) 44 (4.4) 46 (4.4) 21 ( 5.3) 35 (9.6) 28 (5. 9) 32 (4 .9) 20 (7.1) 22 (3.8) 16 (3.0) 14 (3.6) 1 (0.9)
2-3 times/month 77 (8.2) 78 (7.7) 75 (7.1) 38 (9.5) 30 (8.2) 41 (8.6) 54 (8.2) 31 (11.0) 47 (8.2) 37 (6.9) 21 (5.3) 7 (6.0)
1-2 times/week 206 (22.0) 271 (26.8) 269 (25.6) 93 (23.4) 73 (20.1) 125 (26.1) 171 (26.0) 66 (23.4) 133 (23.2) 146 (27.3) 98 (24.9) 27 (23.3)
3 times/week 596 (63.7) 619 (61. 2) 660 (62.9) 246 (61.8) 226 (62.1 ) 284 ( 59.4) 400 (60.9) 165 (58.5) 370 (64.7) 335 (62.7) 260 (66.2) 81 (69.8)
High-fat fish 0.0366 0.0381 0.0720
1 time/month 218 (23.3) 198 (19.6) 196 (18.7) 9 5 (23.9) 96 (26.3) 87 (18.2) 121 (18.4) 65 (23.1 ) 122 (21.3) 111 (20.8) 75 (19.1) 30 (25.9)
2-3 times/month 320 (34.1) 345 (34.1) 331 (31.5) 116 (29.1) 116 (31.8) 164 (34.3) 213 (32.4) 88 (31.2) 204 (35.7) 181 (33.9) 118 (30.0) 28 (24.1)
1-2 times/week 286 (30.5) 347 (34.3) 390 (37.1) 133 (33.4) 107 (29.3) 165 (34.5) 254 (38.7) 96 (34.0) 179 (31.3) 182 (34.1) 136 (34.6) 37 (31.9)
3 times/week 113 (12.1) 122 (12. 1) 133 (12.7) 54 (13.6) 46 (12.6) 62 (13. 0) 69 (10. 5) 33 (11.7) 67 (11.7) 60 (11.2) 64 ( 16.3) 21 (18.1)
High-fat and processed meats < 0.000 1 <0. 0001 < 0.0001
1 time/month 143 (15.3) 60 (5.9) 33 (3.1) 15 (3.8) 50 ( 13.7) 20 (4.2) 19 (2.9) 8 (2.8) 93 (16.3) 40 (7.5) 14 (3.6) 7 (6. 0)
2-3 times/month 264 (28.2) 281 (27.8) 187 (17.8) 71 (17.8) 94 (25.7) 135 (28.2) 113 (17.2) 47 (16.7) 170 (29.7) 146 (27.3) 74 (18.8) 24 (20.7)
1-2 times/week 302 (32.2) 388 (38.3) 474 (45.1) 135 (33.9) 119 (32.6) 190 (39.8) 307 (46.7) 100 (35.5) 183 (32.0) 198 (37.1) 167 (42.5) 35 (30.2)
3 times/week 228 (24.3) 283 (28. 0) 356 (33.9) 177 (44.5) 102 (27.9) 133 (27.8) 21 9 (33.2) 127 (45.0) 126 ( 22.0) 150 (28.1) 138 (35. 1) 50 (43.1)
Sweets and confectionery < 0.000 1 <0. 0001 < 0.0001
1 time/month 98 (10.5) 36 (3.6) 31 (2.9) 21 (5.3 ) 67 (18.4) 25 (5.2) 24 (3.7) 17 (6.0) 31 (5.4) 11 (2 .1) 7 ( 1.8) 4 (3.5)
2-3 times/month 128 (13.7) 151 (14.9) 71 (6.8) 22 (5.5) 69 (18.9) 99 (20.7) 58 (8.8) 21 (7.4) 59 (10.3) 52 (9.7) 13 (3.3) 1 (0.9)
1-2 times/week 220 (23.5) 291 (28.7) 322 (30.7) 61 (15.3) 79 (21.6) 141 (29.5) 226 (34.4) 49 (17.4) 141 (24.6) 150 (28.1) 96 (24.4) 12 (10.3)
3 times/week 491 (52.4) 534 (52. 8) 626 (59.6) 294 (73.9) 150 (41.1) 213 (44.6) 34 9 (53.1) 195 (69.1) 341 ( 59.6) 321 (60.1) 277 (70. 5) 99 (85.3)
Carbonated beverages < 0.0001 < 0.0001 < 0. 0001
1 time/month 354 (37.8) 130 (12.8) 79 ( 7.5) 25 (6.3) 93 (25. 5) 40 (8.4) 34 (5.2) 16 (5.7) 261 (45.6) 90 (16.9) 45 (11.5) 9 (7.8)
2-3 times/month 189 (20.2) 266 (26.3) 118 (11.2) 36 (9.0) 79 (21.6) 110 (23.0) 55 (8.4) 23 (8.2) 110 (19.2) 156 (29.2) 63 (16.0) 13 (11.2)
1-2 times/week 242 (25.8) 346 (34.2) 438 (41.7) 83 (20.8) 110 (30.1) 174 (36.4) 276 (42.0) 56 (19.9) 132 (23.1) 172 (32.2) 162 (41.2) 27 (23.3)
3 times/week 152 (16.2) 270 (26. 7) 415 (39.5) 254 (63.8) 83 (22.7) 154 (32.2) 292 (44.4) 187 (66.3) 69 ( 12.1) 116 (21.7) 123 ( 31.3) 67 (57.8)
Food groups were fruits, vegetables (except Kimchi), milk and dairy products (yogurt /cheese, etc.) , high-fat fish (mackerel/sardines/tuna/herri ng/salmon, etc.), high-fat and processed meats (fresh bacon/beef
ribs/charco al gril led meat/ tripe/ham/sausage/bacon), instant noodle/cup noodle, sweets and confecti onery (cakes/cooki e/pies/candies/chocolates), and carbonated beverages (coke/sprite/ soft
drinks/fruit-flavored drinks except 100% fruit juice).
1) Data are presented as N(%).
2)
P
-value by χ2 test.
Table 2. Other food consumption of study par ticipants according to the frequency of instant noodle consumption1)
Total (N = 3,397) Male (N = 1, 782) Female (N = 1,615)
1
time/month
(N = 937)
2-3
times/ month
(N = 1,012)
1-2
times/week
(N = 1,050)
3
times/week
(N = 398)
P-value2)
1
time/month
(N = 365)
2-3
times/ month
(N = 478)
1-2
times/week
(N = 657)
3
times/week
(N = 282)
P-value2)
1
time/month
(N = 572)
2-3
times/ month
(N = 534)
1-2
times/week
(N = 393)
3
times/week
(N = 116)
P-value2)
WC (cm) 71.5 ± 8.0 72.2 ± 8.6 74.2 ± 8.6 75.2 ± 9.0 0.8453 77.6 ± 7.6 77.7 ± 7.5 78.2 ± 7.8 78.4 ± 8.1 0.7553 67.7 ± 5.4 67.2 ± 6.3 67.6 ± 5.1 67.4 ± 5.7 0.7445
SBP (mmHg) 113.8 ± 14.1 115.5 ± 13.8 119.2 ± 14.0 120.6 ± 13.5 0.2243 124.4 ± 11.6 124.5 ± 11.6 125.4 ± 12.0 125.6 ± 11.6 0.4457 107.1 ± 11.0 107.5 ± 10.3 108.7 ± 10.4 108.6 ± 9. 3 0.5137
DBP (mmHg) 64.2 ± 9.1 65.3 ± 9.2 67.0 ± 9.0 68.1 ± 8.7 0.0216 68.3 ± 8.8 69.3 ± 9.0 69.1 ± 8.7 70.0 ± 8.5 0.1235 61.7 ± 8.3 61.7 ± 7.7 63.4 ± 8.4 63.5 ± 7.3 0.0167
FBS (mg/dL) 83.7 ± 7.6 84.5 ± 7.4 84.9 ± 7.5 86.0 ± 7.7 0.0238 85.7 ± 7.4 85.8 ± 7.6 85.7 ± 7.6 87.0 ± 7.9 0.0687 82.5 ± 7.4 83.4 ± 7.0 83.6 ± 7.3 83.4 ± 6.4 0.5753
TG (mg/dL) 75.4 ± 31. 6 80.3 ± 33.0 81.8 ± 36.1 90.6 ± 53.4 0.0016 83.6 ± 39.6 88.8 ± 3 9.0 87.8 ± 39.9 95.3 ± 58.1 0.0482 70. 1 ± 23.9 72.7 ± 2 4.0 71.7 ± 25.8 79.1 ± 37.4 0.0198
HDL-cholesterol
(mg/dL)
70.6 ± 15. 3 68.3 ± 14.3 66.8 ± 14.7 65.6 ± 14.7 0.1862 62.6 ± 12.9 62.3 ± 1 2.8 62.5 ± 13.1 62.1 ± 13.0 0.8780 75. 7 ± 14.5 73.7 ± 1 3.5 74.1 ± 14.4 74.0 ± 15. 3 0.1452
LDL-cholesterol
(mg/dL)
100.4 ± 27. 9 99.9 ± 2 5.8 99.9 ± 26.1 99.4 ± 25.9 0.7900 97. 6 ± 26.3 100.5 ± 26.3 101.2 ± 27. 1 99.8 ± 26.4 0.2866 102.3 ± 28.7 99.4 ± 25.3 97.7 ±24. 1 98.5 ± 24.9 0.3141
No. of MS
components
0.27 ± 0.5 7 0.30 ± 0.61 0.41 ± 0.68 0.48 ± 0.76 0.3723 0.57 ± 0.73 0.54 ± 0 .75 0.59 ± 0.77 0.62 ± 0.82 0.6297 0. 08 ± 0.31 0.10 ± 0 .33 0.11 ± 0.33 0.15 ± 0.44 0.3720
WC, waist circumference; SBP, systolic blood pressure; DBP, diastolic blood pressure; FBS, fasting blood glucose; TG, triglycerides; MS, metabolic syndrome.
1) Data are presented as mean±SD.
2) Adjusted
P
-value from the general l inear model after controlling for age, BMI, gender, family income (<2000 US $/mo, 2000-4000 US $/mo, >4000 US $/mo), alcohol consumption (non-drinker,
moderate drinker, heavy drinker), smoking behavior (non-smoker, ex-smoker, current smoker), physical activ ity (low, moderate, high), and consumption frequency of fruits, vegetables, milk and dair y
products, high-fat fish, high-fat and processed meats, sweets and confectionery, car bonated beverages (≤ 1 time/month, 2-3 times/month, 1-2 times/week, ≥3 times/week).
Table 3. Metabolic parameters according to the frequency of instant noodle consumption1)
236
Instant noodle and cardiometabolic risk factors
Fig. 1. Numbe r of me tabolic syndrome component s accordi ng to t he fr equency
of instant noodle consumption in all subjects. Reference values for MS components
according to the Adult Treatment Panel III of the National Chol esterol Education Program
(abdominal obesity: males ≥ 90 cm WC, females ≥ 85 cm; elevated blood pressure: SBP
≥ 130 mmHg or DBP ≥ 85 mmHg, hyperglycemia: FBS ≥ 100 mg/dL, hypertriglycemia:
TG ≥ 150 mg/dL, low HDL cholesterol: males <40 mg/dL, females <50 mg/dL). MS,
metabolic syndrome; WC, waist circumference; SBP, systolic blood pressure; DBP,
diastolic blood pressure; FBS, fasting blood glucose; TG, trigl ycerides.
P
-value by χ2 test.
Total (N = 3,397) Male (N = 1,782) Female (N= 1,615)
1
time/month
(N = 937)
2-3
times/ month
(N = 1,012)
1-2
times/week
(N = 1,050)
3
times/week
(N = 398)
P-value
for
trend
1
time/month
(N = 365)
2-3
times /mon th
(N = 478)
1-2
times/week
(N = 657)
3
times/week
(N = 282)
P-value
for
trend
1
time/month
(N = 572)
2-3
times /mon th
(N = 534)
1-2
times/week
(N = 393)
3
times/week
(N = 116)
P-value
for
trend
Abdominal obesity
No. of case (%) 28 (3.0) 36 (3.6) 58 (5.5) 29 (7.3) 25 (6.9) 33 (6. 9) 56 (8.5) 27 (10. 0) 3 (0. 5) 3 (1. 0) 2 (0.5) 2 (1.7)
Multivariate OR
(95% CI)
1 1.316
(0.753-2.300)
1.582
(0.922-2.715)
1.662
(0.887-3.117)
0.3404 1 1.383
(0.763-2.507)
1.679
(0.948-2.972)
1.779
(0.922-3.435)
0.2808 1 0.953
(0.170-5.361)
0.655
(0.084-5.125)
0.882
(0.071-10.964)
0.9798
Elevated blood pressure
No. of case (%) 156 (16.7) 172 (17.1) 260 (24. 8) 109 (27.4) 139 (38.2) 158 (33.2) 241 (36 .8) 105 (37.2) 17 (3.0) 14 (2.6) 19 ( 4.9) 4 (3.5)
Multivariate OR
(95% CI)
1 0.852
(0.639-1.137)
1.036
(0.782-1.372)
0.940
(0.664-1.331)
0.4732 1 0.849
(0.623-1.157)
0.990
(0.734-1.335)
0.930
(0.647-1.338)
0.6519 1 0.799
(0.338-1.899)
1.560
(0.674-3.610)
0.995
(0.254-3.904)
0.4381
Hypergly cemia
No. of case (%) 23 (2.5) 27 (2.7) 26 (2.5) 14 (3.5) 17 (4.7) 19 (4. 0) 18 (2.8) 13 (4.6) 6 (1.1) 8 ( 1.5) 8 (2.0) 1 (0.9)
Multivariate OR
(95% CI)
1 1.092
(0.582-2.050)
1.019
(0.527-1.971)
1.368
(0.631-2.963)
0.8434 1 1.017
(0.473-2.187)
0.834
(0.375-1.856)
1.460
(0.612-3.484)
0.5790 1 1.254
(0.377-4.173)
2.050
(0.599-7.011)
0.639
(0.064-6.366)
0.5571
Hypertriglycemia
No. of case (%) 21 (2.3) 38 (3.8) 62 (5.9) 32 (8.1) 16 (4.4) 30 (6. 3) 56 (8.6) 26 (9.3) 5 (1.0) 8 ( 1.5) 6 (1.5) 6 (5.2)
Multivariate OR
(95% CI)
1 1.685
(0.944-3.011)
2.163
(1.229-3.805)
2.639
(1.393-5.000)
0.0192 1 1.651
(0.844-3.228)
2.089
(1.103-3.955)
2.149
(1.045-4.419)
0.1245 1 2.033
(0.607-6.810)
2.179
(0.566-8.384)
5.992
(1.859-21.824)
0.0346
Low HDL-cholesterol
No. of case (%) 26 (2.8) 35 (3.5) 24 (2.3) 8 (2. 0) 10 (2.8) 16 (3.4) 1 (2 .1) 4 (1.4) 16 ( 2.8) 19 (3.6) 10 ( 2.6) 4 (3.5)
Multivariate OR
(95% CI)
1 1.487
(0.834-2.651)
1.010
(0.527-1.935)
0.786
(0.321-1.923)
0.2948 1 1.473
(0.594-3.654)
0.807
(0.308-2.113)
0.430
(0.114-1.623)
0.1742 1 1.452
(0.676-3.121)
1.152
(0.466-2.851)
1.542
(0.450-5.287)
0.7690
High LDL-cholesterol
No. of case (%) 116 (12.4) 113 (11.2) 126 (1 2.0) 48 (12.1) 44 (12.1) 57 (12.0 ) 96 (14.7) 39 (13.8) 72 ( 12.6) 56 (10.5) 30 (7.7) 9 (7. 8)
Multivariate OR
(95% CI)
1 0.912
(0.674-1.234)
0.920
(0.675-1.254)
0.842
(0.556-1.276)
0.8632 1 1.135
(0.719-1.791)
1.296
(0.840-1.999)
1.230
(0.729-2.075)
0.6874 1 0.824
(0.544-1.246)
0.580
(0.347-0.968)
0.406
(0.162-1.017)
0.0881
Overweig ht (BMI 23)
No. of case (%) 190 (20.3) 246 (24.3) 315 (30. 0) 130 (32.7) 128 (35.1) 197 (41.2) 278 (42 .3) 121 (42.9) 62 (10. 8) 49 (9. 2) 37 (9.4) 9 (7.8)
Multivariate OR
(95% CI)
1 1.095
(0.854-1.405)
1.096
(0.853-1.407)
1.058
(0.770-1.454)
0.8837 1 1.235
(0.910-1.676)
1.217
(0.904-1.638)
1.232
(0.860-1.765)
0.5233 1 0.928
(0.599-1.437)
0.922
(0.564-1.508)
0.613
(0.259-1.452)
0.7443
Metabolic syndrome
No. of case (%) 7 (0.7) 12 (1.2) 16 (1.5) 10 (2.5) 6 (1.6) 12 (2.5) 16 (2.4) 10 (3.6) 1 (0.2) 0 (0.0) 0 (0.0) 0 (0.0)
Multivariate OR
(95% CI)
1 1.565
(0.557-4.401)
1.438
(0.508-4.064)
2.218
(0.713-6.899)
0.5667 1 1.797
(0.602-5.358)
1.665
(0.553-5.009)
2.600
(0.791-8.553)
0.4591 1 - - - -
1) Determined by multivariate logistic regression analysis after controlling for age, BMI, gender, family i ncome (<2000 US $/mo, 2000-4000 US $/mo, >4000 US $/mo), alcohol consumption (non-drinker,
moderate drinker, heavy drinker), smoking behavior (non-smoker, ex-smoker, curr ent smoker ), physical activity (low, moderate, high), and consumption frequency of fruits, vegetabl es, mil k and dairy
products, high-fat fish, high -fat and pr ocessed meats, sweets and confectionery, carbonated beverages (≤ 1 time/month, 2-3 times/month, 1-2 ti mes/week, ≥ 3 t imes/week).
Reference values according to the Adult Treatment Panel III of the National Cholesterol Education Program (abdominal obesity: males ≥90 cm, females ≥ 85 cm; elevated blood pressure: SBP ≥ 130
mmHg or DBP ≥ 85 mmHg, hyperglycemia: FBS ≥ 100 mg/dL; hypertriglycemia: TG ≥ 150 mg/dL, low HDL cholest erol: males <40 mg/dL, females <50 mg/dL, high LDL cholesterol: ≥ 130 mg/dL).
Table 4. Multivariate odds ratios (ORs) and 95% confidence intervals (CIs) for cardiometabolic risk factors according to the frequency of instant noodle consumption1)
blood pressure (P= 0.0216), and fasting blood glucose levels
(P= 0.0238) were higher in the frequent instant noodle consumer
group (3 times/week) than the infrequent consumer group
(1 time/month) after adjusting for the covariates of age, BMI,
gender, family income, alcohol consumption, smoking behavior,
physical activity, and other dietary factors important for
cardiometabolic risk. In female students, triglyceride levels (P
= 0.0198) and diastolic blood pressure (P= 0.0167) were higher
among the frequent consumers of instant noodles. In male
students, triglyceride levels (P= 0.0482) were also higher among
the frequent consumers (Table 3).
Association between the frequency of instant noodle consumption
and cardiometabolic risk factors
College students who consumed instant noodles frequently
were more likely to have multiple cardiometabolic risk factors
(Fig. 1) (P< 0.0001). The proportion of subjects with three or
more risk factors was 0.8% among those who consumed instant
noodles 1 time/month and 2.5% among those who consumed
instant noodles 3 times/week.
As shown in Table 4, multiple logistic regression analysis with
covariates revealed that frequent consumption of instant noodles
In Sil Huh et al.
237
was associated with a higher prevalence of hypertriglyceridemia.
Compared to the group with the lowest frequency of instant
noodle consumption (1 time/month), the OR for hypertrigly-
ceridemia was significantly higher in the groups with a
frequency consumption of 1-2 times/week (OR: 2.163, 95% CI:
1.229-3.805) and 3 times/week (OR: 2.693, 95% CI: 1.393-
5.000) (P for trend = 0.0192) in all subjects. This association was
also observed for males alone (OR: 2.149, 95% CI: 1.045-4.419)
and females alone (OR: 5.992, 95% CI: 1.859-21.824), with a
frequency of instant noodle consumption 3 times/week
compared to 1 time/month. The OR for a high LDL-cholesterol
was significantly lower in the group with a consumption
frequency of 1-2 times/week (OR: 0.580, 95% CI: 0.347-0.968)
compared to the group with the lowest frequency of instant
noodle consumption (1 time/month) in female students only.
DISCUSSION
In this study, we found a positive association between the
frequency of instant noodle consumption and plasma triglyceride
levels, diastolic blood pressure, and fasting blood glucose levels
in Korean college students. Study subjects with a higher
frequency of instant noodle consumption were more likely to
have multiple cardiometabolic risk factors. The OR for hyper-
triglyceridemia was significantly higher in the group that
consumed instant noodles 3 times/week compared to the
group with the lowest consumption frequency (1 time/month).
This association existed in male and female students respectively,
as well as in the combined subjects.
The positive association between instant noodle consumption
and triglyceride levels that we observed among college students
is supported by the results of another recent study conducted
on Korean adults aged 19-64 years. Yeon & Bae [8] showed that
the group with high instant noodle consumption (1 serving/
week) had significantly higher triglyceride levels compared with
the low instant noodle consumption group (< 1 serving/week).
We also found that college students who reported consuming
instant noodles 3 times/week were at a higher risk for
hypertriglyceridemia. We are unable to provide a mechanistic
interpretation of these findings but it is probably due to the
large amounts of carbohydrates and fat contained in instant
noodles. Excess carbohydrate intake is known to increase
triglyceride levels [20].
In our study, diastolic but not systolic blood pressure was
increased, according to the frequency of instant noodle consump-
tion and the effect was more apparent in female students.
Diastolic blood pressure is considered an index of salt sensitivity
[21]. Instant noodles made in Korea contain a significant amount
of sodium in one serving (600-2,770 mg) [22]. According to the
Korea National Health and Nutrition Examination Survey [23],
noodles are one of the main sources of sodium intake in Korea,
and instant noodles comprised the largest proportion of noodles
eaten by South Korean adults in their 20s. If diastolic blood
pressure is an index of salt sensitivity, our data indicate a gender
difference in salt sensitively, such that women may be more
salt-sensitive than men. This needs to be verified though further
studies.
In the present study, a positive association was observed
between instant noodle consumption and fasting blood glucose
levels. This observation is partially consistent with a previous
report [8], which found that instant noodle consumption was
associated with an increased prevalence of hyperglycemia in
Korean women only. Instant noodles are generally high in
refined carbohydrates but low in fiber [2]. This correlates with
the high glycemic index (GI) or the high glycemic load of instant
noodles. Some studies [24,25] have reported that the instant
noodles produced in Korea have a GI of 71-87 and instant
noodles are categorized as a high-GI food.
Although there was no difference in the proportion of
subjects with metabolic syndrome between groups, students
with a higher frequency of instant noodle consumption were
more likely to have multiple cardiometabolic risk factors.
Significant differences were observed in the proportion of
subjects with two risk factors (17.7 vs. 27.6%) and three or more
risk factors (0.7 vs. 2.5%), and between those who consumed
instant noodles 1 time/month vs. 3 times/week. Our findings
suggest that instant noodle consumption might be associated
with the presence of multiple risk factors, even if metabolic
syndrome has not yet manifested because the study subjects
consisted of relatively young individuals.
In this study, we found unexpectedly that the OR for a high
LDL-cholesterol was significantly lower in female students who
consumed instant noodle 1-2 times/week than 1 time/month.
At this point, we do not know whether this is a chance
observation or artifact, therefore, it needs to be explored further
in other studies with different study subjects. Blood levels of
LDL-cholesterol, a well-established cardiometabolic risk factor,
however, has been reported to be influenced by both genes
and the environment, with the genetic factor being stronger
than environmental variables, such as diet [26]. This is one of
the reasons why LDL-cholesterol level is excluded from the
diagnostic criteria of metabolic syndrome.
Researchers at Harvard University reported a 68% higher risk
of metabolic syndrome among women who consume instant
noodles twice/week [1], but not in men. We found that
frequent consumption of instant noodles was associated with
increased diastolic blood pressure in women. These gender
discrepancies might result from differences in food group
compositions in the dietary intake patterns between males and
females [27,28] and the biological differences between males
and females, such as sex hormones and metabolism [27,29].
Previous authors suggested an interaction between bisphenol
A and the estrogen receptor, as a possible contributor to the
gender difference. Bisphenol A is known to be a selective
modulator of estrogen receptors that can accelerate adipogenesis
[30]. Considering that women may be more sensitive to instant
noodle-associated metabolic changes is intriguing. Whether this
is due to bisphenol A found in packaging or to other substances
in instant noodles, warrants further investigation. Meanwhile,
it is advisable to guide young women to minimize their instant
noodle consumption to decrease future CVD metabolic risk.
Unlike fresh ramen noodles, most instant noodles are
deep-fried to dry them, so they are high in calories, refined
carbohydrates, saturated fat, and sodium [2]. The most
consumed [9] type of instant noodles in Korea, for example,
contains 505 kcal and provides 24, 31, 53, and 90% of the
238
Instant noodle and cardiometabolic risk factors
recommended daily values for carbohydrates, fat, saturated fat
and sodium, respectively [2]. Several studies have suggested
that the high energy density, glycemic load (due to the refined
carbohydrates), saturated fat content, and sodium content of
instant noodles, may contribute to increased cardiometabolic
risk factors. South Korea leads the world in per capita
consumption of instant noodles, at 72.8 servings/year, which
is almost six times higher than the world average of 13.5
servings in 2015 [31], with per capita consumption showing an
increasing trend [32]. The convenience and low price of instant
noodles have intensified their popularity in recent decades [32].
The preference for instant noodles is particularly strong among
college students, with time or financial constraints. It has been
reported that among adults of all age groups, younger adults
aged 20-49 years, consume greater amounts of instant noodles
(22.2 g/d) than those aged 50-64 years (7.6 g/d) [33].
The limitations of this study are as follows: first, it was
impossible to define causal associations with this data set
because of the cross-sectional study design. Further prospective
studies are warranted to investigate the causal associations
between instant noodle consumption and cardiometabolic risk
factors. Second, there is a possibility that those who often
consumed instant noodles as a snack, also consumed more
calories overall, which may have led to a higher risk of metabolic
syndrome. However, a previous study [34] observed that most
adults consume instant noodles at lunch or dinner time as a
substitute for a meal instead of a snack. For more accurate
results, controlling participants’ total daily caloric intake and
determining the percentage of total caloric intake fulfilled by
instant noodles is necessary. Despite these limitations, this study
is significant, as it presents homogeneous data collected over
a short duration, which includes data on a large number of
young adults. Although various studies have been conducted
on unhealthy eating habits developed over a long duration in
subjects or patients in their late 40s [35] regarding an increased
risk of cardiometabolic syndrome, insufficient studies have been
conducted to show whether the same results will be seen when
investigating instant noodle intake in younger individuals.
In conclusion, we found that frequent consumption of instant
noodles may be associated with increased cardiometabolic risk
factors among apparently healthy college students aged 18-29
years. Considering the significant, harmful association of multiple
risk factors with increased CVD risk and later development of
CVD, this issue requires immediate attention. It is necessary to
encourage reduced consumption of instant noodles but there
is also a need to educate individuals and for the food industry
to improve the nutritional quality of instant noodles or develop
healthy instant noodles.
CONFLICT OF INTEREST
The authors declare no potential conflicts of interests.
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... At present, there have been studies on the excessive consumption [19,20] of this type of product and the consequences it has for human health; for example, it is related to the appearance of metabolic syndrome, which is manifested in serious disorders in the health of people, such as obesity, blood pressure problems, diabetes, and cholesterol, among others. ...
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Instant soups and noodles are one of the most widely consumed commercial food products. These products are made from ingredients of animal (chicken, meat) and/or vegetable origin, in addition to various food additives that prolong the shelf life of the product. It should be noted that instant soups are a dehydrated product, whose water-removal process can increase the accumulation of contaminants, such as toxic metals (Al, Cd, or Pb), that are harmful to the health of consumers. The content of toxic metals (Al, Cd, and Pb) in a total of 130 samples of instant soups of different types (poultry, meat, and vegetables) was determined by ICP-OES (inductively coupled plasma–optical emission spectrometry). The Al content (32.28 ± 19.26), the Cd content (0.027 ± 0.016), and the Pb content (0.12 ± 0.13) in the vegetable soups were worth mentioning. Considering an intake of twenty grams (recommended by the manufacturer), the dietary intake of Al (19.56% of the TWI set at 1 mg/kg bw/week), the intake of Cd (6.59% of the TWI set at 2.5 µg/kg bw/week), and the Pb intake (16.18% of the BMDL set for nephrotoxic effects at 0.63 µg/kg bw/week and 6.84% of the BMDL set for cardiovascular effects at 1.50 µg/kg bw/week) in the population aged 3–10 years, instant soups are not recommended for the population aged 3–10 years, while their consumption does not pose a health risk for adults. However, it is necessary to consider the cooking water used in the preparation of these products, as it may increase exposure to these toxic metals, in addition to the rest of the diet.
... In addition, genetics is a risk factor for hypertension [21]. Instant noodles, which contain a high volume of salt and high concentration of refined carbohydrates, contribute to high diastolic blood pressure, high TG level, and high fasting blood glucose levels even among college students [22]. Patients with impaired glucose tolerance consuming a diet containing > 45% carbohydrates show a greater postprandial glucose spike [23]. ...
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Background Intracerebral hemorrhage (ICH) and acute ischemic stroke (AIS) have common vascular risk factors; however, ICH often occurs in adults aged < 70 years. Intracerebral hemorrhage and AIS in adults aged < 70 years should be preventable; however, it is unclear why different subtypes of ICH or AIS occur among adults aged < 70 years with vascular risk factors. This study aimed to identify independent variables for ICH or AIS onset in patients aged < 70 years. Methods We included patients aged 40–69 years who experienced ICH or AIS between August 2016 and July 2019. Patients aged < 40 years were excluded because other diseases, rather than vascular risk factors, are often associated with stroke etiology in this age group. Data on age, systolic blood pressure (SBP), serum lipids, and serum fatty acid levels were compared between patients with ICH and those with AIS. In addition, we conducted multivariable logistic regression analyses to identify independent factors among the variables, such as blood pressure or biomarkers, with significant differences between the two groups. Results Of the 1252 acute stroke patients screened, 74 patients with ICH and 149 patients with AIS met the inclusion criteria. After excluding variables with multicollinearity, SBP, glycated hemoglobin (HbA1c), and eicosapentaenoic acid (EPA) proportion (%) of total fatty acids were identified as independent factors affecting ICH and AIS. The SBP and EPA% threshold values for ICH compared to AIS were ≥ 158 mmHg and ≤ 2.3%, respectively. The HbA1c threshold value for AIS compared to ICH was ≥ 6.1%. Conclusions Systolic blood pressure, HbA1c, and EPA%, were independent factors between ICH and AIS. Patients aged 40–69 years with high SBP and low EPA% were at a higher risk of ICH than AIS, and those with a high HbA1c were at a higher risk of AIS than ICH.
... In addition, men's instant noodles and tofu consumption are more different than women abroad. According to Huh et al., 29 males are also more likely to consume instant noodles. Subjects who frequently consumed instant noodles had lowerincome, more physical activity, and were more likely smokers. ...
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The current study investigated the effect of replacing wheat flour with starchy root vegetables in dried tofu noodles on texture, color, antioxidant capacity, and starch digestibility. The Lotus root was selected as a replacement for wheat flour (5%, 10%) based on antioxidant capacity among various starchy root vegetables such as smilax china, lotus root, taro, and yam. Dried tofu noodles added 5% (W65L5T30) and 10% (W60L10T30) lotus root powder did not show any difference in springiness, but their hardness decreased compared to control (W70T30) after cooking. Changes in lightness (ΔL*) increased while its yellowness (Δb*) decreased according to the added amount of lotus root powder due to the oxidation of phenolic components by polyphenol oxidase. However, the antioxidant capacity expressed as trolox equivalent (TE, μmol TE /g dw) was maintained after cooking. In the enzymatic starch hydrolysis, the lowest amount (11.21 ± 1.25%) of rapidly digestible starch (RDS) and the highest amount (57.80 ± 3.13%) of resistant starch (RS) were observed in W60L10T30. After gelatinizing for 20 min, the content of free glucose was 3.56, 3.39, and 3.17% for W70T30, W65L5T30, and W60L10T30, respectively. Results from the current study suggest that lotus root powder as a replacement for wheat flour in dried tofu noodles could be effective not only in improving texture and antioxidant capacity but also in delaying starch digestion after cooking. Lotus root powder could be a potential ingredient that can replace wheat starch in dried tofu noodles as a low glycemic index food, meal replacement for diabetes.
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Background Mediterranean diets have been reported to improve psoriasis. Asian food has a unique character and differs from Mediterranean diets. Methods This study compared the dietary intake of psoriatic patients and individuals without psoriasis, and investigated the association between diet and psoriasis severity. Data were collected on the frequency of consumption of Mediterranean and Asian diets. Results One-hundred psoriatic patients and 100 individuals (age- and sex-matched controls) was conducted. In the case of the anti-inflammatory diets, the psoriatic patients consumed significantly less olive oil, berry fruits, fish, seafood, tree nuts, and eggs than the controls. As to the pro-inflammatory diets, greater quantities of dairy products and soft drinks were consumed by the psoriatic patients than the controls. Regarding Asian food, the patients consumed significantly less pickled foods and brown rice/Riceberry (a rice variety), but more coconut milk, than the controls. In terms of psoriasis severity, the patients with lower severities consumed significantly more vegetables; in contrast, a higher consumption of red meat, belly meat, and instant noodles was associated with greater psoriasis severities. Conclusions Our study adds further information on the role of diets—especially Asian diets—and psoriasis. These data should help patients and clinicians to focus more clearly on diet management.
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Purpose: The aim of this study was to investigate the relationship between instant noodle intake and metabolic factors in Korean adults. Methods: Study subjects were 5,894 (male 2,293, female 3,601) aged 19-64 years who participated in the 2013-2014 KNHANES. Information on frequency and consumption of instant noodles was obtained by the food frequency questionnaires method in KNHANES (Korean National Health and Nutrition Examination Survey), and subjects were classified according to age, sex, and instant noodle consumption (INC). Results: The frequency and consumption of instant noodles was 1.2 times/week and 1.2 servings in subjects. High INC group (? 1 serving/week) was significantly younger in age compared with the low INC group (< 1 serving/week). However, the high INC group had significantly higher waist circumference, metabolic factors (triglyceride, cholesterol, and HDL-cholesterol), and dietary intake (energy intake, fat, and sodium density) compared with the low INC group. Hyperglycemia showed association with higher risk of highest quartile of INC after adjustments for multiple confounding factors, including age, gender, household income, education, smoking, and alcohol compared with the lowest quartile (OR: 1.4, 95% CI: 1.1-1.8). In female, abdominal obesity showed association with higher risk of highest quartile of INC after adjustments for multiple confounding factors compared with the lowest quartile (OR: 1.6, 95% CI: 1.2-2.2). Conclusion: Consumption of instant noodles was associated with increased prevalence of abdominal obesity and hyperglycemia in women. These findings suggest an association of instant noodle consumption status with metabolic risk.
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Background: Fish consumption may prevent or improve metabolic health. The aim of this study was to identify associations between fish consumption, both fatty and lean, and metabolic syndrome and its components. Methods: Associations between fish consumption and metabolic syndrome and its components were studied in a large sample from a Norwegian population (N = 23,907), using cross-sectional data from the Tromsø 4 survey (1994-1995). Metabolic syndrome was defined using the JIS definition, and dietary data was collected using food frequency questionnaires (FFQ). Blood samples were taken for biochemical assessments, and anthropometric and blood pressure measurements were carried out according to standard protocols. Results: In this sample from an adult population (aged 26-70 years, mean age 44 years, SD 11.69, 48 % men), a higher fish consumption (≥1/week) was associated with a healthier lipid profile with increased HDL-C and decreased TG. Participants aged 60-70 years consuming fish once a week or more had significantly lower risk of having MetS, compared to those consuming fish less than once a week (OR 0.64, CI 0.45-0.91). When investigating fatty and lean fish separately, only lean fish consumption was associated with a reduced the risk of having MetS. Participants aged 60-70 years consuming lean fish once a week or more, had lower risk of having MetS compared to those consuming lean fish less than once a week (OR 0.65, CI 0.48-0.87). No association was found for consumption of fatty fish, or for lean fish in the age groups <45 or 45-59 years. Conclusions: These results indicates that fatty and lean fish consumption influences MetS risk differently, possibly also related to age. However, further investigation is needed to establish how various fish consumption may influence MetS and its components, particularly when stratified by fatty and lean fish.
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The impact of sugar consumption on health continues to be a controversial topic. The objective of this review is to discuss the evidence and lack of evidence that allows the controversy to continue, and why resolution of the controversy is important. There are plausible mechanisms and research evidence that supports the suggestion that consumption of excess sugar promotes the development of cardiovascular disease (CVD) and type 2 diabetes (T2DM) both directly and indirectly. The direct pathway involves the unregulated hepatic uptake and metabolism of fructose, leading to liver lipid accumulation, dyslipidemia, decreased insulin sensitivity and increased uric acid levels. The epidemiological data suggest that these direct effects of fructose are pertinent to the consumption of the fructose-containing sugars, sucrose and high fructose corn syrup (HFCS), which are the predominant added sugars. Consumption of added sugar is associated with development and/or prevalence of fatty liver, dyslipidemia, insulin resistance, hyperuricemia, CVD and T2DM, often independent of body weight gain or total energy intake. There are diet intervention studies in which human subjects exhibited increased circulating lipids and decreased insulin sensitivity when consuming high sugar compared with control diets. Most recently, our group has reported that supplementing the ad libitum diets of young adults with beverages containing 0%, 10%, 17.5% or 25% of daily energy requirement (Ereq) as HFCS increased lipid/lipoprotein risk factors for CVD and uric acid in a dose-response manner. However, un-confounded studies conducted in healthy humans under a controlled, energy-balanced diet protocol that enables determination of the effects of sugar with diets that do not allow for body weight gain are lacking. Furthermore, recent reports conclude that there are no adverse effects of consuming beverages containing up to 30% Ereq sucrose or HFCS, and the conclusions from several meta-analyses suggest that fructose has no specific adverse effects relative to any other carbohydrate. Consumption of excess sugar may also promote the development of CVD and T2DM indirectly by causing increased body weight and fat gain, but this is also a topic of controversy. Mechanistically, it is plausible that fructose consumption causes increased energy intake and reduced energy expenditure due to its failure to stimulate leptin production. Functional magnetic resonance imaging (fMRI) of the brain demonstrates that the brain responds differently to fructose or fructose-containing sugars compared with glucose or aspartame. Some epidemiological studies show that sugar consumption is associated with body weight gain, and there are intervention studies in which consumption of ad libitum high-sugar diets promoted increased body weight gain compared with consumption of ad libitum low- sugar diets. However, there are no studies in which energy intake and weight gain were compared in subjects consuming high or low sugar, blinded, ad libitum diets formulated to ensure both groups consumed a comparable macronutrient distribution and the same amounts of fiber. There is also little data to determine whether the form in which added sugar is consumed, as beverage or as solid food, affects its potential to promote weight gain. It will be very challenging to obtain the funding to conduct the clinical diet studies needed to address these evidence gaps, especially at the levels of added sugar that are commonly consumed. Yet, filling these evidence gaps may be necessary for supporting the policy changes that will help to turn the food environment into one that does not promote the development of obesity and metabolic disease.
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Cardiovascular diseases (CVD) are growing contributors to global disease burdens, with epidemics of CVD advancing across many regions of the world which are experiencing a rapid health transition. Diet and nutrition have been extensively investigated as risk factors for major cardiovascular diseases like coronary heart disease (CHD) and stroke and are also linked to other cardiovascular risk factors like diabetes, high blood pressure and obesity. The interpretation of evidence needs to involve a critical appraisal of methodological issues related to measurement of exposures, nature of outcome variables, types of research design and careful separation of cause, consequence and confounding as the basis for observed associations. Adequate evidence is available, from studies conducted within and across populations, to link several nutrients, minerals, food groups and dietary patterns with an increased or decreased risk of CVD. Dietary fats associated with an increased risk of CHD include trans–fats and saturated fats, while polyunsaturated fats are known to be protective. Dietary sodium is associated with elevation of blood pressure, while dietary potassium lowers the risk of hypertension and stroke. Regular frequent intake of fruits and vegetables is protective against hypertension, CHD and stroke. Composite diets (such as DASH diets, Mediterranean diet, ‘prudent’ diet) have been demonstrated to reduce the risk of hypertension and CHD. Sufficient knowledge exists to recommend nutritional interventions, at both population and individual levels, to reduce cardiovascular risk. That knowledge should now be translated into policies which promote healthy diets and discourage unhealthy diets. This requires coordinated action at the level of governments, international organizations, civil society and responsible sections of the food industry.
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Objective: The production and consumption of instant noodles is constantly increasing because of its taste and convenience. However, instant noodle is estimated to be a major contributor to high dietary sodium intake. The purpose of this study is to assess the sodium content of instant noodle and its daily intake by Korean adolescents and adults. Methods: The sodium contents of 214 instant noodle types in the present market were surveyed, and the daily sodium intake from ramen of 1,947 adolescents aged 12 - 18 years and 12,933 adults aged 19 - 64 years was analyzed using 2010 - 2012 Korean National Health and Nutritional Examination Survey data. Results: The sodium contents were 1,483.7 mg/100 g for bag ramen (n = 65), 836.4 mg/100 g for bag ramen without soup (n = 25), 1,752.6 mg/100 g for cup ramen (n = 88), and 945.8 mg/100 g for cup ramen without soup (n = 36). The daily sodium intakes from instant ramen were 281.7 mg (5.5% of total sodium intake) for adolescent boys, 169.4 mg (4.1%) for adolescent girls, 181.6 mg (3.0%) for adult men, and 99.8 mg (2.3%) for adult women. Conclusion: The present results indicate that efforts to reduce sodium content of instant noodle and its intake are needed for healthy diet and reduction of total sodium intake.
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The association of dairy products consumption with risk of metabolic syndrome (MetS) has been inconsistently reported in observational studies. A systematic review and meta-Analysis of published observational studies was conducted to quantitatively evaluate this association. Relevant studies were identified by searching PubMed and EMBASE databases and by carefully checking the bibliographies of retrieved full reports and related reviews. Eligible studies were observational studies that investigated the association between dairy products consumption and risk of MetS in adults, with risk estimates available. Random-effects model was assigned to calculate the summary risk estimates. The final analysis included 15 cross-sectional studies, one case-control study and seven prospective cohort studies. Higher dairy consumption significantly reduced MetS by 17% in the cross-sectional/case-control studies (odds ratioâ €‰=â €‰0.83, 95% confidence interval [CI], 0.73-0.94), and by 14% (relative risk [RR]â €‰=â €‰0.86, 95% CI, 0.79-0.92) in cohort studies. The inverse dairy-MetS association was consistent in subgroup and sensitivity analyses. The dose-response analysis of the cohort studies conferred a significant 6% (RRâ €‰=â €‰0.94, 95% CI, 0.90-0.98) reduction in the risk of MetS for each increment in dairy consumption of one serving/d. No significant publication bias was observed. Our findings suggest an inverse dose-response relationship between dairy consumption and risk of MetS.