Content uploaded by Yangbo Sun
Author content
All content in this area was uploaded by Yangbo Sun on May 01, 2019
Content may be subject to copyright.
SPECIAL FOCUS ISSUE: CARDIOVASCULAR HEALTH PROMOTION
Association of Skipping Breakfast With
Cardiovascular and All-Cause Mortality
Shuang Rong, MD, PHD,
a,b
Linda G. Snetselaar, PHD,
b
Guifeng Xu, MD,
b
Yangbo Sun, MD, PHD,
b
Buyun Liu, MD, PHD,
b
Robert B. Wallace, MD,
b
Wei Bao, MD, PHD
b,c,d
ABSTRACT
BACKGROUND Skipping breakfast is common among U.S. adults. Limited evidence suggests that skipping breakfast is
associated with atherosclerosis and cardiovascular disease.
OBJECTIVES The authors sought to examine the association of skipping breakfast with cardiovascular and all-cause mortality.
METHODS This is a prospective cohort study of a nationally representative sample of 6,550 adults 40 to 75 years of age
who participated in the National Health and Nutrition Examination Survey III 1988 to 1994. Frequency of breakfast
eating was reported during an in-house interview. Death and underlying causes of death were ascertained by linkage
to death records through December 31, 2011. The associations between breakfast consumption frequency and
cardiovascular and all-cause mortality were investigated by using weighted Cox proportional hazards regression models.
RESULTS Among the 6,550 participants (mean age 53.2 years; 48.0% male) in this study, 5.1% never consumed
breakfast, 10.9% rarely consumed breakfast, 25.0% consumed breakfast some days, and 59.0% consumed breakfast
every day. During 112,148 person-years of follow-up, 2,318 deaths occurred including 619 deaths from cardiovascular
disease. After adjustment for age, sex, race/ethnicity, socioeconomic status, dietary and lifestyle factors, body mass
index, and cardiovascular risk factors, participants who never consumed breakfast compared with those consuming
breakfast everyday had hazard ratios of 1.87 (95% confidence interval: 1.14 to 3.04) for cardiovascular mortality
and 1.19 (95% confidence interval: 0.99 to 1.42) for all-cause mortality.
CONCLUSIONS In a nationally representative cohort with 17 to 23 years of follow-up, skipping breakfast was
associated with a significantly increased risk of mortality from cardiovascular disease. Our study supports the
benefits of eating breakfast in promoting cardiovascular health. (J Am Coll Cardiol 2019;73:2025–32)
© 2019 by the American College of Cardiology Foundation.
Cardiovascular disease (CVD) remains the
leading cause of death in the United States
and worldwide. Over the past decades,
numerous dietary and lifestyle risk factors have
been identified for CVD morbidity and mortality,
forming the basis of the American Heart Association’s
Diet and Lifestyle Recommendations for Americans.
However, previous dietary studies have focused
mainly on dietary compositions and their
combinations, such as dietary fats, seafood, and Med-
iterranean diet pattern, and so on. Less is known
about the impact of common eating behaviors on
CVD outcomes.
Breakfast is believed to be an important meal of
the day, whereas there has been an increasing prev-
alence of skipping breakfast over the past 50 years in
the United States, with as many as 23.8% of young
people skipping breakfast every day (1–3). However,
ISSN 0735-1097/$36.00 https://doi.org/10.1016/j.jacc.2019.01.065
From the
a
Department of Nutrition and Food Hygiene, School of Public Health, Medical College, Wuhan University of Science and
Technology, Wuhan, China;
b
Department of Epidemiology, College of Public Health, University of Iowa, Iowa City, Iowa;
c
Obesity
Research and Education Initiative, University of Iowa, Iowa City, Iowa; and the
d
Fraternal Order of Eagles Diabetes Research
Center, University of Iowa, Iowa City, Iowa. The authors have reported that they have no relationships relevant to the contents of
this paper to disclose.
Manuscript received September 3, 2018; revised manuscript received December 8, 2018, accepted January 8, 2019.
Listen to this manuscript’s
audio summary by
Editor-in-Chief
Dr. Valentin Fuster on
JACC.org.
JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY VOL.73,NO.16,2019
ª2019 BY THE AMERICAN COLLEGE OF CARDIOLOGY FOUNDATION
PUBLISHED BY ELSEVIER
studies on the health effects of skipping
breakfast are sparse. Accumulating evidence,
although still limited, suggests that skipping
breakfast is associated with increased risk of
overweight/obesity (2,4), dyslipidemia (5,6),
hypertension (7,8), type 2 diabetes (9,10),
metabolic syndrome (11),coronaryheartdis-
ease (12), and cerebrovascular disease (13).It
is imperative to understand the long-term
health impact of skipping breakfast on cardio-
vascular mortality in the general population.
The aim of our study was to examine the
association of skipping breakfast with cardio-
vascular and all-cause mortality in a nationally
representative cohort in the United States.
METHODS
STUDY POPULATION. The National Health and Nutri-
tion Examination Survey (NHANES), conducted by
the National Center for Health Statistics (NCHS) at the
Centers for Disease Control and Prevention (CDC), is a
large-scale, multistage, ongoing, nationally repre-
sentative health survey of the civilian noninstitu-
tionalized population in the United States (14–16).
Each survey participant completed a household
interview followed by a physical examination in a
mobile examination center. NHANES has been
approved by the NCHS Ethics Review Board. Written
informed consent was obtained from all participants.
In this study, we used data from NHANES III
(1988 to 1994), because information on breakfast
eating was available during that period. NHANES III
was conducted in two 3-year phases (1988 to 1991
and 1991 to 1994). Of the 39,695 participants in the
NHANES III, 33,994 (86%) were interviewed in their
homes by trained staff. Seventy-eight percent
(30,818) of the selected persons were examined in the
mobile examination center, and an additional 493
persons were given a special, limited examination in
their homes. Detailed descriptions of NHANES III
procedures, interviewing, questionnaires and data
collection, quality control techniques, survey design,
nonresponse, and sample weighting have been
described extensively (17,18).
We included participants 40 to 75 years of age who
were free of a history CVD or cancer disease at base-
line and had mortality follow-up information
including underlying cause of death. Considering in-
dividuals at exceptionally high risk of death may
change their dietary intake, and therefore, their diet
information may no longer represent their habitual
consumption, we excluded those who died within
12 months of their NHANES III health examination.
After further exclusion of participants who were
pregnant, who had missing information on frequency
of breakfast consumption, and who had daily total
energy intake <500 kcal or >5,000 kcal, 6,550 sub-
jectswereincludedastheanalyticalsample.
OUTCOME ASCERTAINMENT. We used the NHANES
III Public-Use Linked Mortality File through
December 31, 2011, which was linked by the NCHS to
the National Death Index with a probabilistic match-
ing algorithm to determine the mortality status (19).
National Death Index is an NCHS centralized database
of all deaths in the United States. Data about under-
lying cause of death were used for case definition
according to the 9th Revision International Statistical
Classification of Diseases (ICD-9) through 1998, and
the remainder for case definition according to the
10th Revision (ICD-10). In order to adjust for changes
between the 2 coding systems, final causes of deaths
occurring before 1999 were recorded into comparable
ICD-10–based underlying-cause-of-death groups (19).
The NCHS classified mortality from heart diseases,
including acute rheumatic fever and chronic rheu-
matic heart diseases (codes I00–I09), hypertensive
heart disease (codes I11), hypertensive heart and renal
disease (codes I13), ischemic heart diseases (codes
I20–I25) and other heart diseases (codes I26–I51), and
mortality from cerebrovascular disease (i.e., stroke)
(codes I60–I69) according to ICD-10 (20).Wedefined
deaths from CVD as death from either heart disease or
cerebrovascular disease. Follow-up of participants
continued until death, with censoring at the time of
death for those who died of causes other than CVD, or
on December 31, 2011, for those who survived.
Follow-up time for each person was calculated as the
difference between the NHANES III examination date
and the last known date alive or censored from the
NHANES III mortality file.
EXPOSURE MEASUREMENT. All participants were
asked “How often do you eat breakfast?”during the
household interview, and the possible answers
included “every day,”“some days,”“rarely,”“never,”
and “weekends only.”We merged the answer “week-
ends only”into the category “some days”for analysis.
Finally, the frequency of breakfast eating was classi-
fied as “never,”“rarely,”“some days,”and “every day.”
COVARIATE ASSESSMENT. Information on age, sex,
race/ethnicity, family income, smoking status, alco-
holic intake, and physical activity was collected using
standardized questionnaires during interviews. Race/
ethnicity was classified as non-Hispanic white, non-
Hispanic black, Mexican American, or other. Marital
status was categorized as married (married and living
SEE PAGE 2033
ABBREVIATIONS
AND ACRONYMS
BMI =body mass index
CDC =Centers for Disease
Control and Prevention
CI =confidence interval
CVD =cardiovascular disease
HEI–2010 =Healthy Eating
Index–2010
HR =hazard ratio
ICD =International Statistical
Classification of Diseases
NCHS =National Center for
Health Statistics
NDI =National Death Index
NHANES =National Health and
Nutrition Examination Survey
Rong et al.JACC VOL. 73, NO. 16, 2019
Skipping Breakfast and Mortality APRIL 30, 2019:2025–32
2026
as married), widowed, divorced, and single (never
married and separated). Family income-to-poverty
ratios were categorized as #1.30, 1.31 to 3.50, and
>3.50. A higher income-to-poverty ratio represents a
higher family income status. Participants were cate-
gorized as nonsmoker, past smoker, and current
smokers based on their responses to questions about
smoking at least 100 cigarettes during their lifetime
and whether they were currently smoking. The
amount of alcohol consumed was determined based
on the responses to 2 survey queries that questioned
thenumberofdaysofdrinkingoverthepast
12 months and the number of drinks per day on a
given drinking day (21). Current alcohol intake was
categorizedasnone(0g/day),moderatedrinking(0.1
to 27.9 g/day for men and 0.1 to 13.9 g/day for
women), and heavy drinking ($28 g/day for men
and $14 g/d for women) (22). For physical activity,
theinactivegroupwasdefined as those with no re-
ported leisure time physical activity, the active group
was defined as those who had recommended levels of
physical activity (23) (i.e., self-reported leisure time
moderate activity [metabolic equivalents ranging
from 3 to 6] of 5 or more times per week or leisure
time vigorous activity [metabolic equivalents >6] 3 or
more times per week), and the insufficiently active
group was defined as those who were not inactive and
did not meet the criteria for recommended levels of
physical activity. Dietary information was collected
through 24-h dietary recall interviews. Total energy
intake was calculated using the U.S. Department of
Agriculture Automated Multiple-Pass Method. We
used the Healthy Eating Index–2010 (HEI–2010) to
indicate the overall quality of diet (HEI–2010 score
from 0 to 100, with 100 being the best-quality diet)
(24).
Measurements of height, weight, and blood pres-
sure were performed following a standardized pro-
tocol. Body mass index (BMI) was calculated as
weight in kilograms divided by height in meters
squared (kg/m
2
,<25, 25 to 29.9, $30) (18).Hyper-
tension was defined as currently taking antihyper-
tensive medication, or if not, having systolic blood
pressure level $130 mm Hg and/or diastolic blood
pressure level $80 mm Hg, according to the 2017
American College of Cardiology/American Heart As-
sociation hypertension guidelines (25).Diabeteswas
defined as having been diagnosed with diabetes or
currently taking insulin or were taking diabetes pills,
or having a hemoglobin A
1c
level $6.5% or a fasting
plasma glucose level $126 mg/dl (26). Dyslipidemia
was defined as having a physician’s diagnosis or
currently taking cholesterol-lowering medications, or
having a triglyceride level $150 mg/dl or high-density
lipoprotein cholesterol level <40 mg/dl based on
recommendations by the National Cholesterol Edu-
cation Program Adult Treatment Panel III (27).
STATISTICAL ANALYSIS. All statistical analyses
accounted for the complex, multistage, stratified, and
cluster-sampling design (including oversampling of
certain subpopulations) of NHANES by using sample
weights, strata, and primary sampling units
embedded in the NHANES data. Means and pro-
portions of baseline characteristics were compared by
using linear regression for continuous variables and
logistic regression for categorical variables. The as-
sociations between breakfast consumption frequency
and cardiovascular and all-cause mortality were
investigated by using Cox proportional hazards
regression models with the following covariates: age,
sex, and race/ethnicity (model 1); model 1 plus marital
status,familyincomelevel,smokingstatus,alcohol
intake, and physical activity (model 2); model 2 plus
total energy intake and overall diet quality indicated
by HEI–2010 (model 3). We further adjusted for BMI,
hypertension (yes/no), diabetes (yes/no), and dysli-
pidemia (yes/no) in a separate model (model 4). We
have checked model assumptions for all the analyses.
All statistical analyses were conducted using survey
modules of SAS software version 9.4 (SAS Institute,
Cary, North Carolina). Two-sided p values <0.05 was
considered statistically significant.
RESULTS
Among the 6,550 participants 40 to 75 years of age
(mean age 53.2 years, SE 0.3; 48.0% male) in this
study, 5.1% (n ¼336) never consumed breakfast,
10.9% (n ¼713) rarely consumed breakfast, 25.0%
(n ¼1,639) consumed breakfast some days, and 59.0%
(n ¼3,862) consumed breakfast every day. During
112,148 person-years of follow-up (median follow-up
18.8 years; maximum follow-up 23 years), 2,318
deaths occurred including 619 deaths from CVD. As
shown in Table 1, participants who never consumed
breakfast were more likely to be non-Hispanic black,
former smokers, heavy drinkers, unmarried, physi-
cally inactive, and with less family income, lower
total energy intake, and poorer dietary quality, when
compared with those who regularly ate breakfast. As
shown in Table 2, participants who never consumed
breakfast were more likely to have obesity, and
higher total blood cholesterol level than those who
consumed breakfast regularly.
Participants who never consumed breakfast were
at higher risk for death from CVD. After adjustment
forage,sex,andrace/ethnicity,participantswho
never consumed breakfast had a 75% higher risk of
JACC VOL. 73, NO. 16, 2019 Rong et al.
APRIL 30, 2019:2025–32 Skipping Breakfast and Mortality
2027
all-cause mortality (hazard ratio [HR]: 1.75; 95% con-
fidence interval [CI]: 1.46 to 2.10) and 2.58-fold higher
risk of cardiovascular mortality(HR:2.58;95%CI:
1.64 to 4.06) compared with those who consumed
breakfast every day. In the fully adjusted model, the
multivariable-adjusted HRs for all-cause mortality
and cardiovascular mortality for participants who
never consumed breakfast were 1.19 (95% CI: 0.99 to
1.42) and 1.87 (95% CI: 1.14 to 3.04), respectively
(Table 3, Central Illustration). Sensitivity analysis
excluding participants with diabetes yielded similar
results for both all-cause mortality and CVD mortality
(data not shown).
We further examined the associations of
breakfast eating with heart disease–specificand
stroke-specific mortality separately (Table 4).
Comparedwiththosewhoconsumedbreakfast
every day, participants who never consumed
breakfast had a higher risk of heart disease–specific
mortality (HR: 2.34; 95% CI: 1.44 to 3.80) and
stroke-specific mortality (HR: 3.53; 95% CI: 1.40 to
8.95) in models adjusted for age, sex, race/ethnicity
(Table 4). In the fully-adjusted model, the associa-
tion between skipping breakfast and heart disease-
specific mortality was moderately attenuated and
became non-significant(HR:1.59;95%CI:0.90to
TABLE 1 Baseline Demographic and Lifestyle Characteristics of the Study Population, Accordin g to the Frequency of
Breakfast Consumption
Frequency of Breakfast Consumption
pValue
Every Day
(n ¼3,862)
Some Days
(n ¼1,639)
Rarely
(n ¼713)
Never
(n ¼336)
Mean age, yrs 55.62 0.31 49.47 0.40 49.54 0.40 52.82 0.85 0.005
Sex, %
Male 45.81 1.05 52.59 1.53 49.49 3.06 46.40 4.22 0.030
Female 54.19 1.05 47.41 1.53 50.51 3.06 53.60 4.22
Race/ethnicity, %
Non-Hispanic white 79.77 1.43 75.69 1.75 79.18 1.82 68.62 4.14 <0.001
Non-Hispanic black 7.98 0.52 14.73 1.09 11.56 1.14 13.20 1.67
Hispanic 4.16 0.39 4.34 0.35 3.57 0.36 4.13 0.75
Other 8.09 1.24 5.24 1.12 5.69 1.32 14.05 4.11
Marital status, %
Married 73.92 1.01 73.93 1.58 73.24 2.46 68.60 4.08 0.593
Widowed 7.80 0.57 6.42 0.81 6.94 1.19 9.99 2.10
Divorced 10.30 0.90 11.43 1.15 13.43 1.88 12.43 2.24
Single 7.89 0.64 8.06 0.91 6.31 1.35 8.65 3.49
Ratio of family income to poverty, %
#1.30 7.71 0.73 8.80 1.32 9.26 1.62 12.30 2.92 0.193
1.31–3.50 34.59 1.40 35.22 1.90 33.87 2.54 41.76 3.96
>3.50 50.45 1.88 50.39 2.36 50.56 3.43 38.71 3.56
Missing 7.25 0.55 5.59 0.84 6.32 1.56 7.23 2.25
Smoking status, %
Nonsmoker 47.63 1.40 36.00 1.36 29.75 2.95 24.84 3.32 <0.001
Current smoking 34.82 1.09 30.27 1.52 33.70 3.21 26.86 4.03
Former smokers 17.56 1.01 33.73 1.57 36.55 3.59 48.30 4.32
Alcohol drinking status, %*
Nondrinker 76.42 1.24 72.11 2.29 66.24 3.41 70.12 3.61 <0.001
Moderate drinking 7.96 0.78 8.03 1.09 7.98 1.93 5.07 1.27
Heavy drinking 11.17 1.01 15.92 1.68 21.44 2.52 17.22 2.53
Missing 4.44 0.64 3.95 0.84 4.34 1.19 7.59 2.69
Physical activity, %
Inactive 13.84 0.96 14.76 1.30 15.56 1.58 28.34 2.55 <0.001
Insufficient 41.39 1.59 50.95 1.66 50.00 2.49 34.93 2.94
Recommended level 44.77 1.77 34.29 1.63 34.44 2.57 36.74 4.19
Mean total energy intake, kcal/day 2,010.85 24.99 2,097.99 32.81 2,022.21 43.43 1,733.58 54.70 <0.001
Mean HEI–2010 68.08 0.40 61.30 0.58 60.40 0.67 57.53 1.17 <0.001
Values are weighted mean SE for continuous variables or weighted % SE for categorical variables. *Nondrinker: 0 g/day; moderate drinking: 0.1 to 27.9 g/day for men and
0.1 to 13.9 g/day for women; heavy drinking: $28 g/day for men and $14 g/day for women.
HEI–2010 ¼Healthy Eating Index–2010.
Rong et al.JACC VOL. 73, NO. 16, 2019
Skipping Breakfast and Mortality APRIL 30, 2019:2025–32
2028
2.80). However, the association between skipping
breakfast and stroke-specific mortality remained
significant (HR: 3.39; 95% CI: 1.40 to 8.24).
DISCUSSION
In this large prospective study of a nationally repre-
sentative cohort with 17 to 23 years of follow-up,
we found that skipping breakfast was significantly
associated with an increased risk of cardiovascular
mortality, especially stroke-specific mortality. The
association was independent of demographic, socio-
economic, dietary, and lifestyle factors; BMI; and
cardiovascular risk factors.
To the best of our knowledge, this is the first pro-
spective analysis of skipping breakfast and risk of
cardiovascular mortality. Our findings are generally
in line with previous studies on the relationship
between breakfast eating and CVD incidence. A
cohort of male U.S. health professionals showed that
men who skipped breakfast had a 27% higher risk of
coronary heart disease compared with men who ate
breakfast (12). Another prospective cohort study of a
Japanese general population indicated 14%, 18%,
and 36% greater risks for incident total CVD, total
stroke, and hemorrhage stroke, respectively, among
those skipping breakfast (13). A cross-sectional anal-
ysis performed within the Progression of Early Sub-
clinical Atherosclerosis study indicated that skipping
breakfast was associated with increased odds for
prevalent noncoronary and generalized atheroscle-
rosis independently of the presence of conventional
cardiovascular risk factors (28). Recently, habitual
breakfast skippers were found at increased risk for
development of coronary artery disease and hyper-
tension in Western India (29). In addition, longitudi-
nal studies also showed that skipping breakfast
may have detrimental effects on cardiometabolic risk
factors, including general obesity, abdominal obesity,
metabolic syndrome, hypertension, and higher fast-
ing insulin, total cholesterol, and low-density lipo-
protein cholesterol concentrations (6,11).Taken
together,thesestudiesaswellasourfindings
TABLE 2 Distribution of CVD Risk Factors of the Study Population, According to the Frequency of Breakfast Consumption
CVD Risk Factors
Frequency of Breakfast Consumption
Every Day
(n ¼3,862)
Some Days
(n ¼1,639)
Rarely
(n ¼713)
Never
(n ¼336) p Value
BMI categories, %
<25.0 37.45 1.44 33.88 1.70 38.34 3.13 35.09 3.75 0.001
25.0–29.9 37.21 1.23 37.43 2.07 33.98 2.50 29.53 3.41
$30.0 25.23 1.16 28.65 1.74 27.65 2.50 34.21 4.16
Hypertension, % 54.97 1.16 51.48 1.76 53.21 3.13 53.15 4.04 0.050
DBP, mm Hg 76.46 0.23 77.45 0.41 77.78 0.50 77.14 0.68 0.269
SBP, mm Hg 127.79 0.48 125.10 0.74 125.49 0.86 127.50 1.43 0.919
Diabetes, % 15.14 0.99 10.75 1.12 8.91 1.58 17.13 3.00 <0.001
Fasting glucose, mg/dl 104.24 0.90 100.84 1.20 100.55 2.02 107.56 3.31 0.338
Dyslipidemia, % 46.70 1.85 46.90 1.85 41.39 2.60 47.75 4.02 0.199
TC, mg/dl 216.09 1.41 214.05 1.53 220.59 2.02 225.72 3.51 0.005
LDL-c, mg/dl 135.39 1.61 135.72 1.86 140.54 2.58 141.19 6.55 0.304
HDL-c, mg/dl 50.81 0.51 49.74 0.63 52.35 0.98 50.98 1.50 0.478
TG, mg/dl 161.54 4.77 153.61 3.59 148.03 6.87 167.40 7.41 0.690
Values are weighted % SE for categorical variables or weighted mean SE for continuous variables.
BMI ¼body mass index; CVD ¼cardiovascular disease; DBP ¼diastolic blood pressure; HDL-c ¼high-density lipoprotein cholesterol; LDL-c ¼low-density lipoprotein
cholesterol; SBP ¼systolic blood pressure; TC ¼total cholesterol; TG ¼triglycerides.
TABLE 3 Associations of Breakfast Consumption Frequency With Cardiovascular and
All-Cause Mortality in U.S. Adults 40 to 75 Years of Age
Frequency of Breakfast Consumption
Every Day Some Days Rarely Never
CVD mortality
Deaths/person-yrs 415/64,594 114/29,290 49/12,655 41/5,609
Unadjusted 1 (ref) 0.55 (0.39–0.77) 0.63 (0.39–1.01) 1.79 (1.02–3.15)
Model 1 1 (ref) 1.09 (0.80–1.49) 1.29 (0.80–2.08) 2.58 (1.64–4.06)
Model 2 1 (ref) 0.96 (0.70–1.32) 1.10 (0.67–1.81) 1.93 (1.16–3.19)
Model 3 1 (ref) 0.94 (0.67–1.31) 1.10 (0.67–1.80) 1.84 (1.12–3.03)
Model 4 1 (ref) 0.95 (0.67–1.33) 1.13 (0.68–1.86) 1.87 (1.14–3.04)
All-cause mortality
Deaths/person-yrs 1,533/64,594 462/29,290 198/12,655 125/5,609
Unadjusted 1 (ref) 0.67 (0.56–0.80) 0.67 (0.53–0.84) 1.27 (0.99–1.64)
Model 1 1 (ref) 1.18 (1.01–1.38) 1.22 (0.95–1.55) 1.75 (1.46–2.10)
Model 2 1 (ref) 1.01 (0.86–1.19) 1.01 (0.77–1.30) 1.23 (1.02–1.49)
Model 3 1 (ref) 1.00 (0.84–1.18) 0.98 (0.75–1.27) 1.17 (0.96–1.42)
Model 4 1 (ref) 1.00 (0.85–1.18) 0.99 (0.76–1.28) 1.19 (0.99–1.42)
Values are n or weighted hazard ratio (95% confidence interval). Model 1: adjusted for age, sex, and race/
ethnicity. Model 2: model 1 þmarital status, family income level, smoking status, alcohol intake, physical activity.
Model 3: model 2 þtotal energy intake and overall diet quality indicated by Healthy Eating Index-2010. Model 4:
model 3 þbody mass index, hypertension, diabetes mellitus, and dyslipidemia.
CVD ¼cardiovascular disease.
JACC VOL. 73, NO. 16, 2019 Rong et al.
APRIL 30, 2019:2025–32 Skipping Breakfast and Mortality
2029
underscore the importance of eating breakfast as a
simple way to promote cardiovascular health and
prevent cardiovascular morbidity and mortality.
Skipping breakfast is related to less daily total en-
ergy intake. In this study, participants who never
consumed breakfast had 14% less daily total energy
intake,comparedwiththosewhoconsumedbreakfast
every day. However, the reduced calorie intake may
not explain the observed association between skip-
ping breakfast and higher risk of cardiovascular
mortality, because animal studies and some previous
epidemiological studies have reported protective
effects of caloric restriction on reducing the risk of
chronic diseases and mortality (30,31). Several
mechanisms may explain how skipping breakfast may
induce cardiometabolic abnormalities and ultimately
lead to cardiovascular mortality. First, skipping
breakfast, which is related to changes in appetite and
decreased satiety, might lead to overeating later and
impairment in insulin sensitivity (32–34). By contrast,
eating breakfast has a beneficial effect on appetite
regulation and also improves the glycemic response
at the next eating occasion with increased sensitivity
to insulin (35,36). Second, skipping breakfast was
CENTRAL ILLUSTRATION Hazard Ratios for Mortality From All Causes, Cardiovascular Disease, Heart Disease,
and Stroke Based on Frequency of Breakfast Consumption
Cause of Death
Cardiovascular disease
Every day
Some days
Rarely
Never
All-cause
Every day
Some days
Rarely
Never
Heart disease
Every day
Some days
Rarely
Never
Stroke
Every day
Some days
Rarely
Never
1 (ref)
0.95 (0.67 to 1.33)
1.87 (1.14 to 3.04)
1.13 (0.68 to 1.86)
1 (ref)
1.00 (0.85 to 1.18)
1.19 (0.99 to 1.42)
0.99 (0.76 to 1.28)
1 (ref)
0.90 (0.61 to 1.34)
1.59 (0.90 to 2.80)
1.22 (0.72 to 2.08)
1 (ref)
1.11 (0.53 to 2.32)
3.39 (1.40 to 8.24)
0.66 (0.26 to 1.66)
Hazard Ratios (95% CI)
9.08.07.06.05.0
Hazard Ratios and 95% Confidence Interval
4.03.02.01.00.0 10.0–1.0
Rong, S. et al. J Am Coll Cardiol. 2019;73(16):2025–32.
Hazard ratios were adjusted for age, sex, race/ethnicity, marital status, family income level, smoking status, alcohol intake, physical activity, total energy intake, overall
diet quality indicated by Healthy Eating Index–2010, body mass index, hypertension, diabetes mellitus, and dyslipidemia. Horizontal lines represent 95% confidence
intervals. CI ¼confidence interval.
Rong et al.JACC VOL. 73, NO. 16, 2019
Skipping Breakfast and Mortality APRIL 30, 2019:2025–32
2030
associated with stress-independent overactivity in
the hypothalamic-pituitary-adrenal axis because of a
longer period of fasting, leading to elevated blood
pressure in the morning (7). Eating breakfast has also
been shown to help lower blood pressure (37,38),
which in turn may prevent blood vessel clogging,
hemorrhage, and cardiovascular events. Third, skip-
ping breakfast might also induce deleterious changes
in lipid levels, such as higher total cholesterol and
atherogenic low-density lipoprotein cholesterol con-
centrations, which are independent risk factors of
atherosclerosis (6,28).Fourth,skippingbreakfastmay
be a behavioral marker for unhealthy dietary and
lifestyle habits (39). However, in this study, we have
adjusted for a variety of dietary and lifestyle factors
including smoking, alcohol drinking, physical activ-
ity, total energy intake, and overall diet quality, and
the association between skipping breakfast and car-
diovascular mortality remained significant.
STUDY STRENGTHS. The major strengths of this
population-based study are the use of a nationally
representative sample, which facilitates generaliza-
tion of the findings to the general population in the
United States, the long-term follow-up period of up to
23 years, and the low rates of unmatched records in
the NHANES III Linked Mortality File. In addition,
with the comprehensive data collected in NHANES III,
we were able to control potential confounding effects
from a variety of demographic, socioeconomic, life-
style, and dietary factors.
STUDY LIMITATIONS. First, we did not have infor-
mation about what foods and beverages NHANES III
participants consumed for breakfast. Beyond the
health benefits of eating breakfast compared with
skipping breakfast, it is interesting to understand
how different choices of foods and beverages for
breakfast will affect mortality risk. Second, we were
not able to assess the effects of changes in breakfast
eating habits during the follow-up on cardiovascular
and all-cause mortality, because information on
breakfast eating in NHANES III was collected only at
baseline. Third, the NHANES III Linked Mortality File
identified causes of death through linkage to the
NationalDeathIndex,whichisbasedondeathcer-
tificates. Although this approach has been previously
validated by the CDC and used in many CDC reports
or relevant published reports, we could not rule out
the possibility of errors in classification of the cause
of death. Finally, although we have adjusted for many
potential confounders, we could not completely rule
out the possibility of residual confounding by un-
measured factors.
CONCLUSIONS
In this large prospective study of U.S. adults 40 to 75
years of age, we found that skipping breakfast was
significantly associated with an increased risk of
death from CVD. Our study supports the benefits of
eating breakfast in promoting cardiovascular health.
ACKNOWLEDGMENTS The authors thank the partic-
ipants and staff of the National Health and Nutrition
Examination Survey III 1988 to 1994 for their valuable
contributions.
ADDRESS FOR CORRESPONDENCE: Dr. Wei Bao,
Department of Epidemiology, College of Public
Health, University of Iowa, 145 North Riverside Drive,
Room S431 CPHB, Iowa City, Iowa 52242. E-mail:
wei-bao@uiowa.edu. Twitter: @UIowaCPH.
TABLE 4 Associations of Breakfast Consumption Frequency With Heart Disease and
Stroke Mortality in U.S. Adults 40 to 75 Years of Age
Frequency of Breakfast Consumption
Every Day Some Days Rarely Never
Heart disease mortality
Deaths/person-yrs 312/64,594 88/29,290 39/12,655 33/5,609
Unadjusted 1 (ref) 0.55 (0.37–0.81) 0.71 (0.42–1.21) 1.61 (0.90–2.87)
Model 1 1 (ref) 1.09 (0.76–1.56) 1.45 (0.86–2.45) 2.34 (1.44–3.80)
Model 2 1 (ref) 0.94 (0.65–1.36) 1.22 (0.71–2.09) 1.71 (0.99–2.98)
Model 3 1 (ref) 0.90 (0.62–1.33) 1.19 (0.69–2.03) 1.58 (0.90–2.78)
Model 4 1 (ref) 0.90 (0.61–1.34) 1.22 (0.72–2.08) 1.59 (0.90–2.80)
Stroke mortality
Deaths/person-yrs 103/64,594 26/29,290 10/12,655 8/5,609
Unadjusted 1 (ref) 0.55 (0.29–1.05) 0.32 (0.14–0.73) 2.57 (0.90–7.35)
Model 1 1 (ref) 1.09 (0.55–2.12) 0.66 (0.28–1.55) 3.53 (1.40–8.95)
Model 2 1 (ref) 1.01 (0.51–2.00) 0.59 (0.24–1.46) 2.99 (1.21–7.40)
Model 3 1 (ref) 1.07 (0.53–2.15) 0.64 (0.26–1.59) 3.25 (1.34–7.90)
Model 4 1 (ref) 1.11 (0.53–2.32) 0.66 (0.26–1.66) 3.39 (1.40–8.24)
Values are n or weighted hazard ratio (95% confidence interval). Model 1: adjusted for age, sex, and race/
ethnicity. Model 2: model 1 þmarital status, family income level, smoking status, alcohol intake, and physical
activity. Model 3: model 2 þtotal energy intake and overall diet quality indicated by Healthy Eating Index-2010.
Model 4: model 3 þbody mass index, hypertension, diabetes mellitus, and dyslipidemia.
PERSPECTIVES
COMPETENCY IN MEDICAL KNOWLEDGE: Regularly skip-
ping breakfast in a middle-aged and older population without
known CVD is associated with an increased risk of death from
CVD.
TRANSLATIONAL OUTLOOK: Further studies are needed to
elucidate the biological mechanisms underlying this association
to optimize the impact of a targeted intervention that might
improve cardiovascular health.
JACC VOL. 73, NO. 16, 2019 Rong et al.
APRIL 30, 2019:2025–32 Skipping Breakfast and Mortality
2031
REFERENCES
1. Haines PS, Guilkey DK, Popkin BM. Trends in
breakfast consumption of US adults between 1965
and 1991. J Am Diet Assoc 1996;96:464–70.
2. Deshmukh-Taskar P, Nicklas TA, Radcliffe JD,
O’Neil CE, Liu Y. The relationship of breakfast
skipping and type of breakfast consumed with
overweight/obesity, abdominal obesity, other
cardiometabolic risk factors and the metabolic
syndrome in young adults. The National Health
and Nutrition Examination Survey (NHANES):
1999-2006. Public Health Nutr 2013;16:2073–82.
3. Kant AK, Graubard BI. 40-year trends in meal
and snack eating behaviors of American adults.
J Acad Nutr Diet 2015;115:50–63.
4. van der Heijden AA, Hu FB, Rimm EB, van
Dam RM. A prospective study of breakfast con-
sumption and weight gain among U.S. men.
Obesity (Silver Spring) 2007;15:2463–9.
5. Farshchi HR, Taylor MA, Macdonald IA. Delete-
rious effects of omitting breakfast on insulin
sensitivity and fasting lipid profiles in healthy lean
women. Am J Clin Nutr 2005;81:388–96.
6. Smith KJ, Gall SL, McNaughton SA, Blizzard L,
Dwyer T, Venn AJ. Skipping breakfast: longitudinal
associations with cardiometabolic risk factors in
the Childhood Determinants of Adult Health
Study. Am J Clin Nutr 2010;92:1316–25.
7. Witbracht M, Keim NL, Forester S, Widaman A,
Laugero K. Female breakfast skippers display a
disrupted cortisol rhythm and elevated blood
pressure. Physiol Behav 2015;140:215–21.
8. Lee TS, Kim JS, Hwang YJ, Park YC. Habit of
eating breakfast is associated with a lower risk of
hypertension. J Lifestyle Med 2016;6:64–7.
9. Ballon A, Neuenschwander M, Schlesinger S.
Breakfast skipping is associated with increased risk
of type 2 diabetes among adults: a systematic
review and meta-analysis of prospective cohort
studies. J Nutr 2019;149:106–13.
10. Bi H, Gan Y, Yang C, Chen Y, Tong X, Lu Z.
Breakfast skipping and the risk of type 2 diabetes:
a meta-analysis of observational studies. Public
Health Nutr 2015;18:3013–9.
11. Odegaard AO, Jacobs DR Jr., Steffen LM, Van
Horn L, Ludwig DS, Pereira MA. Breakfast fre-
quency and development of metabolic risk. Dia-
betes Care 2013;36:3100–6.
12. Cahill LE, Chiuve SE, Mekary RA, et al. Pro-
spective study of breakfast eating and incident
coronary heart disease in a cohort of male US
health professionals. Circulation 2013;128:337–43.
13. Kubota Y, Iso H, Sawada N, Tsugane S,
Group JS. Association of breakfast intake with
incident stroke and coronary heart disease: the
Japan Public Health Center-Based Study. Stroke
2016;47:477–81.
14. National Center for Health Statistics. Plan and
Operation of the Third National Health and
Nutrition Examination Survey (NHANES III, 1988-
94): Reference Manuals and Reports: Weighting
and Estimation Methodology Report. Hyattsville,
MD: Centers for Disease Control and Prevention,
1998.
15. National Center for Health Statistics. National
Health and Nutrition Examination Survey: NHANES
Questionnaires, Datasets, and Related Documen-
tation. Available at: https://wwwn.cdc.gov/nchs/
nhanes/Default.aspx. Accessed January 28, 2012.
16. Ahluwalia N, Dwyer J, Terry A, Moshfegh A,
Johnson C. Update on NHANES dietary data: focus
on collection, release, analytical considerations,
and uses to inform public policy. Adv Nutr 2016;7:
121–34.
17. National Center for Health Statistics, U.S.
Department of Health and Human Services.
NHANES III Reference Manuals and Reports (CD-
ROM). Hyattsville, MD: Centers for Disease Con-
trol and Prevention, 1996.
18. Plan and operation of the Third National
Health and Nutrition Examination Survey, 1988-
94. Series 1: programs and collection procedures.
Vital Health Stat 1 1994:1–407.
19. National Center for Health Statistics. NCHS
2011 Linked Mortality Files Matching Methodol-
ogy. Hyattsville, MD: Office of Analysis and
Epidemiology, 2013.
20. World Health Organization. International Sta-
tistical Classification of Diseases and Related
Health Problems: Tenth Revision. 2nd edition.
Geneva, Switzerland: World Health Organization,
2004.
21. Liangpunsakul S. Relationship between alcohol
intake and dietary pattern: findings from NHANES
III. World J Gastroenterol 2010;16:4055–60.
22. U.S. Department of Agriculture and U.S.
Department of Health and Human Services. 2015–
2020 Dietary Guidelines for Americans. 8 edition.
Washington, DC: U.S. Government Printing Office,
2015.
23. Pate RR, Pratt M, Blair SN, et al. Physical ac-
tivity and public health. A recommendation from
the Centers for Disease Control and Prevention
and the American College of Sports Medicine.
JAMA 1995;273:402–7.
24. Retnakaran R, Qi Y, Connelly PW, Sermer M,
Hanley AJ, Zinman B. Low adiponectin concen-
tration during pregnancy predicts postpartum in-
sulin resistance, beta cell dysfunction and fasting
glycaemia. Diabetologia 2010;53:268–76.
25. Whelton PK, Carey RM, Aronow WS, et al. 2017
ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/
NMA/PCNA guidelinefor the prevention, detection,
evaluation,and management of high bloodpressure
in adults: executive summary: a report of the
American College of Cardiology/American Heart
Association Task Force on Clinical Practice Guide-
lines. J Am Coll Cardiol 2018;71:2199–269.
26. Menke A, Casagrande S, Geiss L, Cowie CC.
Prevalence of and trends in diabetes among adults
in the United States, 1988-2012. JAMA 2015;314:
1021–9.
27. National Cholesterol Education Program
(NCEP). Expert Panel on Detection Evaluation, and
Treatment of High Blood Cholesterol in Adults
(Adult Treatment Panel III). Third Report of the
National Cholesterol Education Program (NCEP)
Expert Panel on Detection, Evaluation, and
Treatment of High Blood Cholesterol in Adults
(Adult Treatment Panel III) final report. Circulation
2002;106:3143–421.
28. Uzhova I, Fuster V, Fernandez-Ortiz A, et al.
The importance of breakfast in atherosclerosis
disease: insights from the PESA study. J Am Coll
Cardiol 2017;70:1833–42.
29. Sharma K, Shah K, Brahmbhatt P, Kandre Y.
Skipping breakfast and the risk of coronary artery
disease. QJM 2018;111:715–9.
30. Most J, Tosti V, Redman LM, Fontana L. Cal-
orie restriction in humans: an update. Ageing Res
Rev 2017;39:36–45.
31. Ahmet I, Tae HJ, de Cabo R, Lakatta EG,
Talan MI. Effects of calorie restriction on car-
dioprotection and cardiovascular health. J Mol Cell
Cardiol 2011;51:263–71.
32. Alwattar AY, Thyf ault JP, Leidy HJ. T he effect
of breakfast typ e and frequency o f consumption
on glycemic response in overweight/obese l ate
adolescent girl s. Eur J Clin Nutr 2 015;69:
885–90.
33. Astbury NM, Taylor MA, Macdonald IA.
Breakfast consumption affects appetite, energy
intake, and the metabolic and endocrine re-
sponses to foods consumed later in the day in
male habitual breakfast eaters. J Nutr 2011;141:
1381–9.
34. Reutrakul S, Hood MM, Crowley SJ,
Morgan MK, Teodori M, Knutson KL. The rela-
tionship between breakfast skipping, chronotype,
and glycemic control in type 2 diabetes. Chrono-
biol Int 2014;31:64–71.
35. Jovanovic A, Gerrard J, Taylor R. The second-
meal phenomenon in type 2 diabetes. Diabetes
Care 2009;32:1199–201.
36. Gwin JA, Leidy HJ. A review of the evidence
surrounding the effects of breakfast consumption
on mechanisms of weight management. Adv Nutr
2018;9:717–25.
37. Ahuja KD, Robertson IK, Ball MJ. Acute effects
of food on postprandial blood pressure and mea-
sures of arterial stiffness in healthy humans. Am J
Clin Nutr 2009;90:298–303.
38. Peitzman SJ, Berger SR. Postprandial blood
pressure decrease in well elderly persons. Arch
Intern Med 1989;149:286–8.
39. Park S, Rim SJ, Lee JH. Associations between
dietary behaviours and perceived physical and
mental health status among Korean adolescents.
Nutr Diet 2018;75:488–93.
KEY WORDS all-cause mortality,
cardiovascular mortality, skipping breakfast
Rong et al.JACC VOL. 73, NO. 16, 2019
Skipping Breakfast and Mortality APRIL 30, 2019:2025–32
2032
