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Journal of the American Heart Association
J Am Heart Assoc. 2021;10:e020718. DOI: 10.1161/JAHA.120.020718 1
ORIGINAL RESEARCH
Plant- Centered Diet and Risk of Incident
Cardiovascular Disease During Young to
Middle Adulthood
Yuni Choi , PhD; Nicole Larson, PhD; Lyn M. Steffen, PhD; Pamela J. Schreiner , PhD; Daniel D. Gallaher, PhD;
Daniel A. Duprez, MD, PhD; James M. Shikany , DrPH; Jamal S. Rana, MD, PhD; David R. Jacobs, J r, P h D
BACKGROUND: The association between diets that focus on plant foods and restrict animal products and cardiovascular dis-
ease (CVD) is inconclusive. We investigated whether cumulative intake of a plant- centered diet and shifting toward such a diet
are associated with incident CVD.
METHODS AND RESULTS: Participants were 4946 adults in the CARDIA (Coronary Artery Risk Development in Young Adults) pro-
spective study. They were initially 18 to 30years old and free of CVD (1985– 1986, exam year [year 0]) and followed until 2018.
Diet was assessed by an interviewer- administered, validated diet history. Plant- centered diet quality was assessed using the
A Priori Diet Quality Score (APDQS), in which higher scores indicate higher consumption of nutritionally rich plant foods and
limited consumption of high- fat meat products and less healthy plant foods. Proportional hazards models estimated hazard
ratios of CVD associated with both time- varying average APDQS and a 13- year change in APDQS score (difference between
the year 7 and year 20 assessments). During the 32- year follow- up, 289 incident CVD cases were identified. Both long- term
consumption and a change toward such a diet were associated with a lower risk of CVD. Multivariable- adjusted hazard ratio
was 0.48 (95% CI, 0.28– 0.81) when comparing the highest quintile of the time- varying average ADPQS with lowest quintiles.
The 13- year change in APDQS was associated with a lower subsequent risk of CVD, with a hazard ratio of 0.39 (95% CI,
0.19– 0.81) comparing the extreme quintiles. Similarly, strong inverse associations were found for coronary heart disease and
hypertension- related CVD with either the time- varying average or change APDQS.
CONCLUSIONS: Consumption of a plant- centered, high- quality diet starting in young adulthood is associated with a lower risk
of CVD by middle age.
Key Words: cardiovascular disease ■ plant- centered diet ■ prospective cohort study
Heart disease remains the leading cause of death
in the United States.1 Suboptimal diet is a major
risk factor for morbidity and mortality.2 There is a
growing interest in the cardiovascular health benefits
of diets that focus on consuming only plant foods, ex-
cluding animal products. However, the evidence that
such diets actually confer a lower risk of incident car-
diovascular disease (CVD) is inconclusive.3 Recently,
an overall diet quality index that emphasizes healthful
plant- derived foods with restriction of all animal- derived
foods (plant- based diet quality index [PDI]) has been
studied for its association with risk of incident CVD and
mortality, but inconsistent results have been reported
across studies.4– 6 One study reported that improved
the healthful PDI scores over 12years was associated
with a lower subsequent risk of CVD- specific mortal-
ity and all- cause mortality.7 Otherwise, data regarding
the association between change in plant- centered diet
quality and subsequent risk of incident CVD are scarce.
Currently, little is known regarding the association
Correspondence to: David R. Jacobs Jr, PhD, Division of Epidemiology and Community Health, School of Public Health, University of Minnesota– Twin Cities,
Suite 300 West Bank Office Building, 1300 S. 2nd Street, Minnesota, MN 55454- 1015. E- mail: jacob004@umn.edu
Supplementary Material for this article is available at https://www.ahajo urnals.org/doi/suppl/ 10.1161/JAHA.120.020718
For Sources of Funding and Disclosures, see page 11.
© 2021 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley. This is an open access article under the terms of the Creat ive
Commo ns Attri butio n- NonCo mmerc ial- NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use
is non- commercial and no modifications or adaptations are made.
JAHA is available at: www.ahajournals.org/journal/jaha
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J Am Heart Assoc. 2021;10:e020718. DOI: 10.1161/JAHA.120.020718 2
Choi et al Plant- Centered Diet and Cardiovascular Disease
between overall diet quality and risk of incident CVD
during the transition period from young to middle
adulthood because most prospective cohort studies
are initiated in middle age. Yet young adulthood is a
key stage, in which modifying risk factors may greatly
reduce CVD risk in later adulthood.8
The present study evaluated the hypotheses that
long- term consumption of a plant- centered diet
and a shift toward a plant- centered diet starting in
young adulthood are associated with a lower risk of
incident CVD in midlife. Plant- centered diet quality
was assessed using the A Priori Diet Quality Score
(APDQS), in which higher scores represent greater
consumption of nutritionally rich plant foods and
lower consumption of high- fat meat products and
unhealthy plant foods. The APDQS has some re-
semblance to other diet quality indices that gener-
ally emphasize plant foods.4,9 The unique feature of
plant- centeredness in the APDQS is that higher con-
sumption of nutritionally rich plant foods and lower
consumption of unhealthy plant foods and high- fat
red meats are the main contributors to a higher
score; however, certain subsets of animal products
also contribute (eg, low- fat yogurt, cheese, nonfried
fish, or nonfried poultry). The underlying viewpoint of
the APDQS is that dietary practices with more flex-
ible options can ensure that the general population
achieves and maintains a daily healthy eating pat-
tern over long periods of life. Previous epidemiologic
studies support the validity of the APDQS by provid-
ing evidence of its linear associations with clinical
outcomes.10– 13
METHODS
The data that support the findings of this study are
available from the CARDIA Coordinating Center
(https://www.cardia.dopm.uab.edu) upon reasonable
request.
Study Population and Design
CARDIA (Coronary Artery Risk Development in Young
Adults) is a multicenter, prospective cohort study of
5115 Black and White men and women from 4 US cit-
ies. Participants were aged 18 to 30years who were
free of CVD at baseline (1985– 1986, exam year [year
0] clinic exam), with a retention rate of 71% among sur-
vivors at year 30 (2015– 2016).14 At baseline and dur-
ing 8 follow- up examinations, data collection included
laboratory tests, physical measurements, medical
histories, and lifestyle factors. Vital status and mor-
bidity were ascertained biennially through 2018, with
successful contact of >90% of participants over the
past 5years. For the present study, participants were
excluded who reported implausible energy intakes
(<800 or >8000kcal/d for men; <600 or >6000kcal/d
for women; n=133) at year 0, year 7, or year 20 or
who lacked information regarding physical activity
or smoking (n=36). Analyses of the time- varying av-
erage APDQS were based on 4946 participants. For
analysis of the 13- year change in APDQS (year 20–
year 7), the events were followed up since year 20
(2005– 2006; mean age, 45 years); therefore, of the
3549 participants who attended the year 20 examina-
tion, those with CVD at or before year 20 (2005– 2006;
n=57), those with no diet data at year 7 or year 20
(n=846), or those with no physical activity or no smok-
ing at year 7 or year 20 (n=25) were excluded from
the analysis, leaving 2621 participants. All participants
provided written informed consent at all examinations,
CLINICAL PERSPECTIVE
What Is New?
• Our study expands on previous studies by ex-
ploring the time- varying relationship between
plant- centered diet quality and risk of car-
diovascular disease during the transition from
young to middle adulthood.
• An important aspect is clarifying whether a flex-
ible, plant- centered diet improves cardiovas-
cular outcomes, where nutritionally rich plant
foods are the central component of the diet, and
subsets of animal products may be integrated.
• Long- term consumption of a plant- centered
diet and shifting to such a diet, starting in young
adulthood, were associated with a lower cardio-
vascular disease risk.
What Are the Clinical Implications?
• Our findings are consistent with assertions that
a nutritionally rich plant- centered diet help pre-
vent the development of cardiovascular disease.
However, it appears that the complete exclusion
of animal foods from diet is not necessary.
• From a clinical and public health perspective,
our findings support a recommendation of eat-
ing primarily nutritionally rich plant foods, but al-
lowing small amounts of animal products (eg,
low- fat dairy products, nonfried fish, and non-
fried poultry), to prevent early cardiovascular
disease.
Nonstandard Abbreviations and Acronyms
APDQS A Priori Diet Quality Score
CARDIA Coronary Artery Risk Development in
Young Adults
PDI plant- based diet quality index
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J Am Heart Assoc. 2021;10:e020718. DOI: 10.1161/JAHA.120.020718 3
Choi et al Plant- Centered Diet and Cardiovascular Disease
and research protocols were approved by institutional
review boards at the coordinating center and each
CARDIA field center.
Assessment of Plant- Centered Diet
Quality
Diet was assessed via the interviewer- administered
CARDIA diet history questionnaire at year 0, year 7,
and year 20. The diet history established reproduc-
ibility and validity.15 ,16 Trained interviewers asked the
participants about consumption of foods and bev-
erages over the past month within 100 closed food
categories (“Do you eat meat?,” “Do you eat vegeta-
bles?,” etc) and recorded open- ended responses of
specific foods eaten (specific types of foods eaten,
brand names, preparation methods, frequency of
intake, and serving size). The number of food items
recorded in the CARDIA cohort was 950 at year 0,
1388 at year 7, and 4598 at year 20. CARDIA diet
data were analyzed using Nutrition Data System for
Research (University of Minnesota, Minneapolis, MN),
which includes over 18 000 foods of which about
7500 are brand name products and is updated an-
nually to reflect marketplace changes. The Nutrition
Data System for Research summarized foods in 166
food groups (invariant over calendar year), which
CARDIA collapsed into 46 food groups for the pur-
pose of creating the APDQS. Total energy intake was
derived through summing energy intake of all foods,
which was calculated by multiplying consumption of
food (frequency × serving size) by the energy con-
tent of each item using Nutrition Data System for
Research.
Plant- centered diet quality was assessed using the
APDQS, which is a hypothesis- driven index based
on 46 food groups, which are derived from individ-
ual foods collected. The APDQS reflects a theoreti-
cal concept that how foods affect human health does
not act in isolation, but in concert, where nutrients
and bioactive compounds in a mixture of individual
foods consumed over time work together to produce
health outcomes.17 The food groups were classified
into beneficial (20), adverse (13), and neutral (13) on
the basis of their presumed prior known association
with CVD.18,19 There was general, though not per-
fect, agreement of ratings of food groups done inde-
pendently by 4 experts in the field. These ratings used
only prior knowledge of the literature. The beneficially
rated food group includes fruit, avocado, beans/le-
gumes, green vegetables, yellow vegetables, toma-
toes, other vegetables, nuts and seeds, soy products,
whole grains, vegetable oil, fatty fish, lean fish, poultry,
alcohol (beer, wine, and liquor), coffee, tea, and low- fat
milk/cheese/yogurt. In practice, the amount of alcohol
consumed was rarely more than a moderate level. The
adversely rated food group includes fried potatoes,
grain dessert, salty snacks, pastries, sweets, high-
fat red meats, processed meats, organ meats, fried
fish/poultry, sauces, soft drink, whole- fat milk/cheese/
yogurt, and butter. The neutrally rated food group in-
cludes potatoes, refined grains, margarine, chocolate,
meal replacements, pickled foods, sugar substitutes,
lean meats, shellfish, eggs, soups, diet drinks, and
fruit juices. Each of the 46 food groups was divided
into quintiles of consumption and then scores of 0
(quintile 1) to 4 (quintile 5) were assigned to the bene-
ficially rated food groups, while scores of 4 (quintile 1)
to 0 (quintile 5) were assigned to the adversely rated
food groups. Zero points were assigned to the neu-
trally rated food groups. For the foods with many 0
servings/day, participants were divided into 5 groups
based on distribution of 0 and quartile (among con-
sumers). Change in diet of individuals over time were
tracked on the basis of specific cut points for each
food group that had been derived from year 0 CARDIA
data that were applied to the follow- up diet data at
year 7 and year 20. Forty- six component scores were
summed to form the total APDQS score, ranging from
0 (minimum) to 132 (maximum). A previous analysis
in CARDIA showed that participants with the great-
est improvement in the APDQS over time largely in-
creased consumption of beneficially rated plant foods
while reducing consumption of adversely rated meat
products.10
Outcome Ascertainment
Primary outcomes were incident CVD. Cases were
identified through August 31, 2018. CVD encompassed
myocardial infarction, non– myocardial infarction acute
coronary syndrome, stroke, heart failure, carotid or
peripheral artery disease, atherosclerotic coronary
heart disease, other atherosclerotic disease, and non-
atherosclerotic cardiac disease. Coronary heart dis-
ease (CHD) and hypertension- related CVD were also
examined as secondary outcomes. Occurrence of
death was determined by CARDIA staff on the basis
of biannual contact with participants or family mem-
bers and record linkage to the National Death Index.
Following each death, the death certificate, autopsy,
and hospital records were requested with next- of- kin
consent. A panel of 2 physicians reviewed all col-
lected information and determined cause of death by
consensus.
Assessment of Covariates
Updated information regarding demographics, maxi-
mal educational attainment, smoking status, medica-
tion use, and parental history of CVD was self- reported
on standardized questionnaires. Physical activity lev-
els were estimated on the basis of a CARDIA physical
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J Am Heart Assoc. 2021;10:e020718. DOI: 10.1161/JAHA.120.020718 4
Choi et al Plant- Centered Diet and Cardiovascular Disease
activity history questionnaire administered by the in-
terviewer. Physical activity was measured in exercise
units as a product of intensity and frequency based on
13 different physical activities performed over the pre-
vious year.20 Body mass index (BMI) was calculated as
weight/height squared (kg/m2) on the basis of meas-
urements by trained technicians. Diabetes mellitus
was defined as fasting blood glucose ≥126 mg/dL, a
2- hour postchallenge glucose concentration ≥200mg/
dL, glycated hemoglobin ≥6.5%, or taking antidiabetic
medication. Hypertension was defined as systolic or
diastolic blood pressure of ≥130 or ≥80 mm Hg or
taking antihypertensive medications. Dyslipidemia
was defined as serum triglycerides ≥150 mg/dL or
high- density lipoprotein cholesterol <40 for men and
<50mg/dL for women.
Statistical Analysis
Cox proportional hazards regression models were
used to estimate hazard ratios (HRs) and 95% CIs
for CVD associated with the APDQS. Person- years
were calculated from the date of baseline examina-
tion to the date of initial diagnosis of CVD, death,
or the end of follow- up (August 31, 2018), whichever
occurred first. To account for potential changes in
diet over time, the APDQS was modeled as a time-
varying exposure: (1) the year 0, year 7, and year 20
values were cumulatively averaged over follow- up.21
Specifically, year 0 predicted events over follow- up
from year 0 to year 7, the average of year 0 and year
7 predicted events over follow- up from after year 7 to
year 20, and the average of year 0, year 7, and year
20 predicted events over follow- up from after year
20 to year 32. Note that if both year 7 and year 20
diet were missing, the model used year 0 data with
outcomes over all follow- up. This method carries for-
ward part or all of the previously observed values
and has the advantage of updating time trend and
retaining participants throughout follow- up (Data S1);
(2) the year 7 value was subtracted from the year
20 value to calculate the 13- year change in APDQS,
and it was evaluated with the outcomes occurring
after year 20. Analyses of the time- varying aver-
age APDQS evaluated the long- term impact of diet
throughout adulthood, and analyses of the APDQS
change evaluated the dynamic relationship between
an individual’s continuing dietary change during the
transition period from young to middle adulthood
and risk of later disease during midlife. We estimated
the risk of CVD using quintile variables as well as
the per 1- SD (13 points) increment in the APDQS as
continuous variables.
Initial analyses of the time- varying average APDQS
were adjusted for year 0 age, sex, race (White or
Black), total energy intake, and maximal educational
attainment (model 1), and were then further adjusted
for parental CVD history (yes versus no), year 0 smok-
ing status (never, former, and current), and physical
activity (model 2). Total energy intake and physi-
cal activity were treated as time- varying covariates.
Hypertension, diabetes mellitus, dyslipidemia, and
BMI as time- varying variables were further adjusted
for in the model (model 3) to examine whether the
association between APDQS and CVD was poten-
tially mediated by these comorbidities. The media-
tion effect of these clinical variables (cumulative data
through year 7) on the association between year 0
APDQS and CVD was quantified by comparing the
models with and without the mediating variables using
the formula: 1 − (βmediator model/βbase model) × 100.22
Next, we examined the association between the 13-
year change in APDQS and subsequent 12- year risk
of CVD outcomes, adjusting for the same covariates
as in the time- varying average diet analysis and, ad-
ditionally, adjustments for the year 7 APDQS and the
13- year change in total energy and physical activity.
CHD and hypertension- related CVD were also exam-
ined with the APDQS as time- varying or change in
secondary analyses.
We computed restricted cubic splines with 4 knots
to visually assess the shape of association between
ADPQS as a continuous variable (both time- varying
average and 13- year change) and risk of CVD.23 ,24
Statistical significance of nonlinearity (ie, curvature)
was tested by comparing the spline model with the
linear model, and P values of <0.05 were regarded as
statistically significant nonlinear relationship between
the exposure and the outcome. Statistical significance
of linearity was tested by comparing the linear model
to the model including only the covariates, both using
likelihood ratio tests.
Sensitivity analyses assessed the robustness
of the primary findings. First, 5- and 8- year lagged
analyses were performed to minimize the potential
impact of reverse causality attributable to preexist-
ing disease with individual diet variables at year 0,
year 7, and year 20, separately. Second, whether
the association differed by the past diagnoses of hy-
pertension, diabetes mellitus, and dyslipidemia was
evaluated by testing multiplicative terms of each past
diagnosis stratum (yes versus no) and the APDQS
(continuous) added in model 2 using the Wald test.
Also, stratified analyses according to race (White or
Black), sex (male or female), education (tertiles split),
physical activity (median split), and smoking (cur-
rent or noncurrent smoker) were performed and the
significance of the interaction were evaluated in the
same way.
All analyses were performed using SAS version 9.4
software (SAS Institute Inc., Cary, NC). The statistical
tests were 2- tailed, with P<0.05 considered to be sta-
tistically significant.
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J Am Heart Assoc. 2021;10:e020718. DOI: 10.1161/JAHA.120.020718 5
Choi et al Plant- Centered Diet and Cardiovascular Disease
RES ULTS
Participants Characteristics
We documented 289 incident CVD cases during
the 32- year follow- up. The mean cumulative APDQS
was 65.1±11.7 (range, 31– 101), and the mean 13- year
change in APDQS was 3.6±10.5 (range, −36 to 51).
Participants with higher APDQS tended to be older,
female, more educated, more physically active, con-
sumed more alcohol, and consumed less energy
as compared with participants with lower APDQS
(Table1). Additionally, participants with higher APDQS
were less likely to self- identify their race as Black,
smoke cigarettes, have a lower BMI, and have a his-
tory of dyslipidemia. The mean intake of each of the 46
food groups by quintiles of the year 0 APDQS is pre-
sented in Table2. To further specify the scoring sys-
tem, the cut points for each of the 46 food groups and
examples of the high and low scores of the APDQS
are shown in TableS1. One participant with a score
of 47 versus 1 participant with a score of 81 were ar-
bitrarily selected as examples of diets at the median
scores of the 2 extreme quintiles of the year 0 data.
While consuming more beneficially rated plant foods
and animal foods was the main driver in increasing
the diet quality score (12- point difference), consuming
less adversely rated plant foods and high- fat red and
processed meats was the driver of the score (22- point
difference).
Association of Plant- Centered Diet Quality
and Risk of Incident CVD outcomes
The time- varying average APDQS was inversely asso-
ciated with incident CVD (HR for quintile 5 versus quin-
tile 1=0.39; 95% CI, 0.23– 0.64; model 1 in Table 3).
Further adjustment for other covariates in model 2 did
not appreciably alter the association (HR for quintile 5
versus quintile 1=0.48; 95% CI, 0.28– 0.81). The asso-
ciation was slightly attenuated after additional adjust-
ment for time- varying hypertension, diabetes mellitus,
dyslipidemia, and BMI (HR for quintile 5 versus quintile
1=0.54; 95% CI, 0.32– 0.93; model 3). In mediation ef-
fect analyses, dyslipidemia explained some of the as-
sociation between the year 0 APDQS and risk of CVD
(15.8% explained; 95% CI, 5.6%– 37.1%; P<0.001), and
hypertension, diabetes mellitus, and BMI did not ex-
plain this association (<5% explained and P>0.05 for
all). Evaluation of specific CVD events showed that the
time- varying average APDQS was strongly associ-
ated with both CHD (HR for quintile 5 versus quintile
1=0.48; 95% CI, 0.24– 0.97) and hypertension- related
CVD (HR for quintile 5 versus quintile 1=0.48; 95% CI,
0.24– 0.94).
An increase in the APDQS over 13years was as-
sociated with a lower risk of CVD in the subsequent
12years in change analyses (HR for quintile 5 ver-
sus quintile 1=0.33; 95% CI, 0.16– 0.68; model 1 in
Table 4). This association was slightly attenuated in
Table 1. Baseline Characteristics ( Year 0) of the Participants According to Quintiles of the Year 0 APDQS* (n=4946)
Characteristics
Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5
P Value†
n=1026 n=999 n=984 n=9 91 n=946
Median of Year 0 APDQS (range) 47 (24 – 51) 55 (52– 58) 62 (59– 65) 7 0 (6 6 – 74) 81 (75 – 107 )
Age, y 23.1±3.7 24.4± 3.7 2 5.1±3. 6 2 5.7± 3.3 26.4±2.9 < 0.001
Female, N (%) 512 (4 9. 9) 527 (52.8) 526 (53.5) 52 6 (5 3.1) 623 (65.9) <0.001
Black race, N (%) 812 (79 .1) 677 (67.8) 5 22 (53.1 ) 365 (36.8) 133 (14.1) <0.001
Maximal educational attainment
(through ye ar 30), grades
14. 2± 2. 3 14.5±2.5 15.1± 2 .6 15.9 ±2.6 16. 9±2.3 <0.001
Physical activit y, EU‡35 7± 278 372±296 4 0 7±28 9 425 ±275 519 ±3 08 <0.001
Current s moker, N (%) 339 (33.0) 341 (34.1) 319 (3 2.4) 275 (27. 8) 196 (20.7 ) <0.0 01
Alcohol intake, drinks/d 0.4 ±1. 0 0.8±1.5 0 .9±1. 8 1.0±1.4 1. 0±1.1 <0.0 01
Energy intake, kcal/d 315 7±1382 2869±1388 28 8 2±146 3 26 92±124 5 2453±1033 <0.0 01
Parental history of CVD 395 (38.5) 398 (39.8) 419 (42 .6 ) 366 (36.9) 382 (4 0.4) 0.12
Prevalent disease
Diabetes mellitus, N (%) 8 (0.8) 5 (0.5) 9 (0.9) 7 (0.7) 4 (0.4) 0.65
Hyper tension, N (%) 40 (3.9) 5 1 (5 .1) 41 (4 .2) 33 (3.3) 28 (3.0) 0 .13
Dyslipidemia, N (%) 299 (29.3) 286 (28.7) 287 (29.4) 274 (27.7 ) 191 (20.3) <0.001
BMI, kg/m224.5±5.5 25±5.5 25.1±5.4 24.5±4.7 23.5±3.7 <0.001
APDQS indicates A Priori Diet Qualit y Score; BMI, body mass index; and CVD, cardiovascular disease.
Values are re ported as the mean±SD, unless noted as No. (percentage).
*Total score sums the 46 components (possible scores 0 – 132, with a range of 35– 95 in these data), with higher scores representing a nu tritionally rich, plant-
centered diet. A 1- point increment represents a one- categor y shif t in the presumed favorable direction.
†Evaluated w ith chi- square tests for categoric al varia bles and ANOVA for continuous variables.
‡Exercise units, physical activity score der ived from the CARDIA physical activit y histor y.
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Choi et al Plant- Centered Diet and Cardiovascular Disease
Table 2. Mean Intake of 46 Individual Food Groups According to Quintiles of the APDQS at Year 0 (n= 494 6)
Food Group
Mean Int ake±SD in Serv ing/D ay
Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5
Beneficially rated
1. Fruit 0. 9 6±1.38 1. 02 ±1.2 3 1. 27±1.4 5 1.5 6±1.55 2.05±1.64
2. Avoc ado 0.01±0.09 0.02±0.09 0.05±0.22 0 .11± 0 .30 0.24±0.47
3. Beans and legumes 0.17±0.35 0.21±0.44 0.21±0.38 0.19±0.32 0.24±0.4
4. Green vegetables 0.12±0.24 0.20±0.34 0.27±0.38 0.42±0.61 0 .9 0 ±1. 2 5
5. Yellow vegetables 0.07±0.21 0.12±0.22 0.2±0.65 0.28±0.52 0.60±0.97
6. Tomato 0.32±0.30 0.38±0.41 0.44±0.47 0.52±0.46 0.73±0.65
7. Other vegetable s 1.42 ±1.17 1.6 4±1.37 2 .0 1±1. 5 8 2 .28 ±1. 64 2.89±2.16
8. Nuts and seeds 0.39±0.84 0.53±1.04 0.79 ±1. 47 0.82±1.44 1.12±1.6 5
9. Soy products 0.09±0.44 0.18±0.65 0.21±0.70 0.23±0.65 0 . 47±1.0 6
10. Whole grains 1.01±1.3 4 1. 20 ±1.3 7 1.4 6±1.45 1.67±1.5 3 2.14±1.7 7
11. Vegetable oil 0. 8 7±1. 2 6 1.2 6±1.56 1.47±1.72 1.6 2±1.71 2.04±2.06
12. Fatty fish 0.01±0.07 0.02±0.09 0.03±0.27 0.03±0.13 0.08±0.25
13. Lean fish 0.44±0.90 0.52±0.79 0.64±1.02 0.84 ±1. 32 1.0 3±1.49
14. Poultry 1.07±1.14 1.0 6±1.0 6 1.17±1.36 1.3 3±1.7 7 1.4 2±1.71
15. B eer 0.29±0.85 0.53±1.24 0.54±1.24 0. 5 6±1.0 6 0.48±0.71
16. W in e 0.04±0.23 0.08±0.3 0 0.14±0.63 0.2±0.39 0.31±0.49
17. Liquor 0.10±0.52 0.16±0.55 0.24±0.63 0.26±0.56 0.18±0.45
18. C of fee 0.46±1.63 0 . 79 ± 2 .13 1.16 ± 2 .4 4 1. 43 ±2.3 1 1.8 5± 2.71
19. Tea 0.3 2±1.27 0.62±5.98 0 . 57±1.46 0 .72±2.76 0.8 5 ± 2.15
20. Low- fat milk/
Cheese/Yogurt
0.55±1.06 0 . 89±1.4 8 1.18±1.96 1.4 6±1.85 1.6 5±1.52
Neutrally rated
1. Pot at oe s 0.38±0.53 0.42±0.59 0.46±0.76 0.41±0.58 0.34±0.40
2. Refined grains 5.62±3.28 4 .60± 3 .12 4.32±3.03 3.8±2.70 3.15± 2 . 22
3. Margarine 1. 67± 2 .48 1. 71±2 .2 7 1.77± 2 .19 1. 74±2 . 41 1.3 9 ±2.0 8
4. Chocolate 0.22±0.37 0.20±0.41 0.20±0.44 0.17±0.45 0.12±0.23
5. Meal replacements 0.01±0.13 0.0 1± 0 .11 0 .01±0 .11 0.02±0.28 0.01±0.07
6. Pickled foods 0.29±0.71 0.29±0.73 0.34±0.55 0.39±0.70 0.40±0.63
7. Sugar substitutes 0.01±0.10 0.04±0.44 0.05±0.27 0.08±0.33 0.13±0.43
8. Lean red meats 0.82±1.10 0 .83 ±1. 0 2 0.92±1.28 0.74±0.99 0.48±0.75
9. Shellfish 0.14±0.38 0.17±0.33 0.21±0.42 0.31±0.94 0.27±0.42
10. Eggs 0.78±0.80 0.72±0.81 0.66±0.75 0.57±0.58 0.49±0.51
11. Soups 0.02±0.06 0.03±0.07 0.04±0.09 0. 0 5 ± 0.11 0.04±0.07
12. Diet soft drinks 0.11±0. 5 9 0.25±0.92 0 . 39 ±1. 0 8 0.55±1.38 0.6 8 ±1.4 4
13. Fruit juice 1.83 ±2 .3 6 1.81±2.58 1.88±2.3 1.93± 2.20 1. 85 ±2 .2 7
Adversely rated
1. Fried potatoes 0.53±0.57 0.38±0.46 0.35±0.51 0.28±0.45 0.15±0.24
2. Grain des serts 0.9 7±1. 2 8 0.65±0.78 0.67±0.80 0.54±0.64 0.46±0.65
3. Salty snacks 0. 0 3 ± 0.11 0.0 4±0.22 0.03±0.12 0.03±0.23 0.04±0.18
4. Pastries 1.23±1.18 1. 02 ±1.12 0. 9 4±1.13 0.79±0.92 0.64±0.72
5. Sweets 2.00±2.46 2.03±2.56 1.8 7± 2.4 4 1.48 ±2 .0 4 0. 9 6 ±1. 36
6. High- fat red meats 2.85± 2 .11 2.59±2.32 2 .41± 2.11 2.09± 2.53 1.16 ±1.6 0
7. Processed meats 1.23 ±1.26 1.0 2±1.12 0.88±1.03 0.67±0.93 0.33±0.63
8. Organ me ats 0.06±0.19 0.05±0.16 0.05±0.18 0.04±0.14 0.02±0.07
9. Fried poultry and fish 0.15±0.84 0.12±0.75 0.11± 0 . 6 8 0.09±0.61 0.07±0.55
(Continued)
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Choi et al Plant- Centered Diet and Cardiovascular Disease
model 2; the highest quintile of 13- year change in
APDQS was associated with a 61% (95% CI, 0.19–
0.81) lower subsequent 12- year risk of CVD as
compared with the lowest quintile. Strong inverse
associations were observed for CHD (HR for quintile
5 versus quintile 1=0.21; 95% CI, 0.06– 0.75; model
2) and hypertension- related CVD (HR for quintile 5
versus quintile 1=0.34; 95% CI, 0.16– 0.74; model 2).
These results were preserved after further adjustment
for comorbidity variables. A monotonic decrease
in CVD risk with time- varying average APDQS (P-
nonlinearity=0.12 and P- linearity<0.001; FigureA) and
the 13- year change in APDQS (P- nonlinearity=0.54
and P- linearity=0.04; FigureB) was observed in re-
stricted cubic splines. Associations between either the
time- varying average APDQS or the 13- year change
in APDQS with CVD did not differ by race, sex, educa-
tion, physical activity, or smoking (P- interaction >0.05
for each).
Sensitivity Analyses
In exam year– specific and exam- lagged analyses (5-
and 8- year lag), an inverse association between the
APDQS as a fixed baseline variable and CVD risk was
observed (TableS2). HR comparing the extreme quin-
tiles was stronger for the year 0 APDQS, although the
gradient of association across categories was more
consistent for the year 20 APDQS. Neither the as-
sociations of the time- varying average APDQS nor of
the 13- year change in APDQS with risk of CVD dif-
fered significantly by histories of hypertension, diabe-
tes mellitus, or dyslipidemia (P- interaction >0.05 for
each).
DISCUSSION
In this 32- year prospective cohort study, which fol-
lowed participants since young adulthood, long- term
consumption of a plant- centered, high- quality diet
that also incorporates subsets of animal products
was associated with a 52% lower risk of incident CVD.
Furthermore, an increase in plant- centered diet quality
over 13years was associated with a 61% lower risk of
incident CVD in the subsequent 12years.
There is increasing interest in understanding the
association between diets that emphasize plant foods
and limit most animal products and incident CVD out-
comes, but the evidence is inconclusive. A previous
meta- analysis showed that vegetarians (versus non-
vegetarians) had a lower risk of ischemic heart dis-
ease, but not incident CVD and all- cause mortality.3
The noted limitations were narrow definitions of popu-
lations, uncertain accuracy of the assessment of veg-
etarian status, and inconsistent results across studies
(the inverse associations were apparent in the US
Adventist cohorts but not in non- Adventist cohorts). In
addition, some studies have defined vegetarian diets
as non– meat eaters on the basis of food frequency in-
take or have self- identified as vegetarians, but neither
approach comprehensively captures an individual’s
overall diet quality. Recently, the healthful PDI has been
developed that focuses on healthy plant foods, limit-
ing all animal- derived foods. In a pooled analysis of 3
large cohorts, higher healthful PDI was associated with
a 14% lower risk of CVD, comparing the highest with
the lowest quintiles.4 Consistent with this, we found
that the time- varying APDQS was associated with a
lower risk of incident CVD, CHD, and hypertension-
related CVD. In contrast, however, another study found
no association with incident CVD.6 The PDI and the
APDQS share some commonalities. Both diet quality
indices assess the overall diet quality in holistic ap-
proaches, differentiating plant foods by their nutritional
quality. On the other hand, there are some differences.
All animal- derived products are rated adversely in the
PDI, while only high- fat processed/unprocessed red
meats, organ meats, and fried fish/poultry are rated
adversely in the APDQS. Additionally, the PDI does
not include alcoholic beverages in the index, while the
APDQS does. An important finding of our study was
to clarify whether eating nutritionally rich plant foods
while integrating subsets of animal products into diet
can improve future cardiovascular outcomes. The sen-
sitivity analyses of previous studies further support
the benefits of these flexible diet characteristics. The
reduced estimate of CHD or total mortality remained
similar when the modified healthful PDI was fitted as
the main exposure, where fish, poultry, dairy products,
or eggs were changed from their original adverse rating
Food Group
Mean Int ake±SD in Serv ing/D ay
Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5
10. Sauces 4.62±4.18 4 .3 1±5 .51 4.67±6.39 4.3 9±5.97 4.72±9.27
11. Soft drinks 2.68±2.59 1. 95 ±2.2 5 1.4 0±1.76 0 .9 8 ±1. 43 0.43±0.74
12. Whole- fat milk/
Cheese/Yogurt
2.51± 2. 37 2 .0 1±1. 87 2.02±2.17 1.74±2.50 1.36 ±1.3 4
13. B utter 6.02±4.66 4.60±4.03 4.44±4.33 3.90±3.600 3.12±3.07
Table 2. Continued
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Choi et al Plant- Centered Diet and Cardiovascular Disease
Table 3. HR (95% CI) of Incident CVD Outcomes ( Year 0– Year 32) According to Q uintiles of t he Time- Varying Average APDQS*
Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5
Each 1- SD increment
(13 - p oint) P for Trend‡
CVD
APDQS (median)†50.0 58.0 64.3 71. 5 81.0
Unadjusted cumulative incidence % (n/N)†9.0 (89/989) 7.8 (77/989) 5. 3 (51/9 61) 4.8 (49/1015) 2.3 (23/992)
Model 1§1 (ref) 0.86 (0.62– 1.17) 0.68 (0.48– 0.96) 0.6 9 ( 0.47– 1.01) 0.39 (0.23– 0.64) 0.74 (0.63– 0.87) <0.001
Model 2|| 1 (ref) 0.87 (0.63– 1.19) 0.73 (0.52– 1.04) 0.78 (0.53– 1.14) 0.48 (0.28– 0.81) 0.80 (0.67– 0.95) 0. 010
Model 3#1 (ref) 0.83 (0.60– 1.15) 0.72 (0.51– 1.03) 0.79 (0.53– 1.16) 0.54 (0.32– 0.93) 0.81 (0.68– 0.96) 0 .018
CHD
APDQS (median)†50.0 58.0 64.3 71. 5 81.0
Unadjusted cumulative incidence % (n/N)†3.7 (37/989) 3.6 (35/985) 3.2 (31/964) 2.2 (22/1016) 1.3 (13/992)
Model 1§1 (ref) 0.82 (0.51– 1.33) 0.82 (0.50– 1.34) 0.54 (0.30– 0.96) 0.38 (0.19– 0.75) 0.72 (0.57– 0.91) 0.006
Model 2|| 1 (ref) 0.84 (0.52– 1.36) 0.91 (0.55– 1.48) 0.63 (0.35– 1.12) 0.48 (0.24– 0.97) 0.78 (0.61– 1.00) 0 .0 51
Model 3#1 (ref) 0.89 (0.54– 1.45) 0.97 (0.59 – 1.61) 0.69 (0.38– 1.25) 0.61 (0.30– 1.25) 0.83 (0.65– 1.07) 0 .15
Hypertensive- related CVD
APDQS (median)†50.0 58.0 64.3 71. 5 81.0
Unadjusted cumulative incidence % (n/N)†7.1 (70/989) 5.4 (53/986) 3.4 (33/964) 3.0 (3 0/1014) 1.3 (13 /99 3)
Model 1§1 (ref) 0.79 (0.55 – 1.15) 0.61 (0.40– 0.93) 0 .7 0 (0. 4 4 – 1 .11) 0.39 (0.20– 0.76) 0.75 (0.61– 0.92) 0.0 06
Model 2|| 1 (ref) 0.80 (0.55– 1.16) 0.65 (0.43– 0.99) 0.78 (0.49– 1.23) 0.48 (0.24– 0.94) 0.80 (0.65– 0.99) 0.040
Model 3#1 (ref) 0.74 (0.51– 1.07) 0.60 (0.39– 0.92) 0.73 (0.46– 1.16) 0.50 (0.25– 0.99) 0.77 (0.62– 0.96) 0.022
APDQS indicates A Priori Diet Qualit y Score; CHD, coronar y hear t disease; CVD, cardiovascular disease; and HR, hazard ratio.
*Time- varying variables that were cumulatively averaged over follow- up at year 0, year 7, and year 20. Specifically, year 0 predicted events ove r follow- up from year 0 to year 7, the average of year 0 and year 7 predicted
events over follow- up from after year 7 to year 20, and the average of year 0, ye ar 7, and year 20 predicted events over follow- up from af ter year 20 to year 32. Note that if both year 7 and ye ar 20 diet was missing, the
model used year 0 data with outcomes over all follow- up.
†Median A PDQS, number of cases, and numbers at risk are categories according to quintiles of the average of all available APDQS measu rements.
‡Statistical significance was estimated by modeling APDQS as a continuous variable in the model.
§Model 1: year 0 age, sex, race (White or Black), total energy intake (time- varying averag e), and maximal educational attainment.
||Model 2: model 1+parental history of CVD (yes vs no), year 0 smoking status (neve r, former, and current), and physic al activity level (time- varying average).
#Model 3: model 2+time- varying comorbidities (hypertension, diabetes mellitus, dyslipidemia [all yes vs no], and body mass index [continuous]).
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Choi et al Plant- Centered Diet and Cardiovascular Disease
Table 4. HR (95% CI) of Incident CVD Outcomes ( Y20- Y32) Accord ing to Quintiles of the 13- year Change in APDQS*
Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5
Each 1- SD increment
(13 - p oint) P for Trend†
CVD
13- year change in APDQS
(median)
−9 −1 4 9 17
Unadjusted cumulative
incidence % (n/N)
5.6 (31/5 59 ) 4.2 (22/522) 2. 5 (13 /52 2) 4 (21/528) 2 . 2 (11/4 9 0 )
Model 1‡1 (ref) 0.74 (0.43– 1.3) 0.42 (0.22– 0.81) 0.63 (0.35– 1.12) 0.33 (0.16 – 0.68) 0.69 (0.52– 0.90) 0.0 07
Model 2§1 (ref) 0.81 (0.46 – 1.43) 0.48 (0.25– 0.93) 0.74 (0.41– 1.33) 0.39 (0.19– 0.81) 0.75 (0.57– 1.00) 0.048
Model 3|| 1 (ref) 0.86 (0.49– 1.5) 0.47 (0.24– 0.92) 0.75 (0.41– 1.35) 0.36 (0.17– 0.75) 0.73 (0.56– 0.97) 0.028
CHD
13- year change in APDQS
(median)
−9 −1 4 9 17
Unadjusted cumulative
incidence % (n/N)
2.9 (16/5 59) 2.1 ( 11/ 522 ) 1.3 (7/5 22 ) 2.1 ( 11/ 528 ) 0.6 (3/490)
Model 1‡1 (ref) 0.71 (0.32– 1.54) 0.43 (0.17– 1.06) 0.66 (0.30– 1.47) 0.18 (0.05– 0.64) 0.64 (0.43 – 0.9 5) 0.027
Model 2§1 (ref) 0.79 (0.36– 1.74) 0.50 (0.20 – 1.24) 0.75 (0.33– 1.69) 0.21 (0.06 – 0.75) 0.70 (0.47– 1.05) 0.084
Model 3|| 1 (ref) 0.83 (0.37– 1.82) 0.53 (0.21– 1.32) 0.77 (0. 34 – 1.75) 0.20 (0.06 – 0.72) 0.69 (0.46– 1.04) 0.076
Hypertensive- related CVD
13- year change in APDQS
(median)
−9 −1 4 9 17
Unadjusted cumulative
incidence % (n/N)
5.0 (28/557) 2.9 (15/ 521) 1.3 ( 7/5 2 2) 2.5 (13/5 27) 2.0 (10/4 90 )
Model 1‡1 (ref) 0.54 (0.29– 1.03) 0.23 (0.10– 0.54) 0.38 (0.19– 0.76) 0.29 (0.14 – 0.64) 0.58 (0.42– 0.79) <0.001
Model 2+ 1 (ref) 0 . 5 8 (0 . 31– 1.11) 0.26 (0.11– 0.61) 0.44 (0.22– 0.89) 0.34 (0.16– 0.74) 0.63 (0.45– 0.86) 0.004
Model 3|| 1 (ref) 0.60 (0.32– 1.15) 0.23 (0.10– 0.54) 0.44 (0.22– 0.90) 0.31 (0.14– 0.68) 0.61 (0.44– 0.84) 0.003
APDQS indicates A Priori Diet Qualit y Score; CHD, coronar y hear t disease; CVD, cardiovascular disease; and HR, hazard ratio.
*The 13- year change in APDQS ( year 20 value minus year 7 value) was used to predict events occurred between year 20 and year 32.
†Statistical significance was estimated by modelling APDQS as a continuous variable in the mode l.
‡Model 1: year 7 APDQS, year 0 age, sex, race (White or Black), total energy intake (year 7 and 13- year change), and ma ximal educational attainment.
§Model 2: model 1+parental history of CVD (yes vs no), year 7 s moking status (never, former, and current), and physical activity level ( year 7 and 13- year change).
||Model 3: model 2+hypertension (yes vs no), diabetes mellitus (yes vs no), dyslipidemia (yes vs no), and body mass index (continuous). The cumulative data through ye ar 20 were used.
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Choi et al Plant- Centered Diet and Cardiovascular Disease
to a beneficial rating.7, 25 Furthermore, consumption of
these types of animal products has not generally been
associated with an increased risk of CVD outcomes
and mortality.26– 31
Longitudinal analyses can provide unique insights
as to whether late- life disease risk can be altered by
changing diet quality over time. Several long- term
prospective studies have demonstrated the relation-
ship between change in diet quality (assessed by the
Healthy Eating Index- 2015, the Alternative Healthy
Eating Index- 2010, the Dietary Approaches to Stop
Hypertension, or the Alternate Mediterranean Diet
score) and subsequent risk of CVD and mortality,
although results have varied.9,32,33 The timing and
duration of exposure to risk factors may differen-
tially affect the development of adult disease.34 Thus,
evaluating diet exposure in middle or older adulthood
may not completely explain the full spectrum of adult
disease development. Our study adds to the current
evidence on the association between diet quality and
CVD risk by indicating that improved plant- centered
diet quality, starting in young adulthood, is associ-
ated with a lower subsequent risk of CVD by middle
adulthood.
It is also worth noting that in the CARDIA sample,
there was a notable difference in the distribution of race
among the lowest versus the highest quintiles of the
APDQS (Black race, 79% versus 14%) and also there
was a difference in the maximal educational attainment
(14.2 versus 16.9 grades completed). We also ob-
served higher CVD cumulative incidence among Black
participants (7.7% for Black versus 3.9% for White)
and individuals with a lower educational level (8.6% for
≤13 grades versus 3.4% for ≥17 grades). Given the ob-
served higher risk of CVD with lower APDQS values,
the results of our study point out that the diet may help
to explain disparities in CVD, although the relationships
of the APDQS and incident CVD did not differ by race
or education. Further studies are warranted to explore
the association between a plant- centered diet and risk
of CVD events, considering these social parameters as
a potential mediator of the relationship.
It is not fully understood how a plant- centered diet has
a protective effect against the development of CVD. As
we previously described, the concerted action of nutri-
ents and bioactive compounds found in a combination
of plant foods may lead to a favorable cardiovascular
outcome.10,17 Numerous compounds, including ascorbic
Figure. Restricted cubic spline cur ves for the association of incident CVD wit h (A) the time- var ying average APDQS
(n=4946) and (B) the 13- year change in APDQS (n=2 621).
A, Time- varying average APDQS and incident CVD. B, 13- year change in APDQS and incident CVD. The solid line is the HR and the
dashed line represents the 95% CI. HR and 95% CI were calculated using restricted cubic splines with 4 knots within proportional
hazard regression models. Nonlinearity was tested by comparing the spline model with the linear model, and linearity was tested by
comparing the linear model to the model including only the covariates, both using likelihood ratio tests. A, Model was adjusted for year
0 age, sex, race (White or Black), total energy intake (time- varying average), maximal educational attainment, parental history of CVD
(yes vs no), year 0 smoking status (never, former, and current), and physical activit y level (time- var ying average). P- nonlinearity=0.12
and P- linearity<0.001. B, Model was adjusted for Y7 APDQS, Y0 age, sex, race (White or Black), total energy intake (year 7 and 13- year
change), and ma ximal educational attainment, parental history of CVD (yes vs no), year 7 smoking status (never, former, and current),
and physical activit y level (year 7 and 13- year change). P- nonlinearity=0.54 and P- linearity= 0.04. APDQS indicates A Priori Diet Quality
Score; CVD, cardiovascular disease; and HR, hazard ratio.
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J Am Heart Assoc. 2021;10:e020718. DOI: 10.1161/JAHA.120.020718 11
Choi et al Plant- Centered Diet and Cardiovascular Disease
acid, tocopherols, carotenoids, and phenolics, are abun-
dant in nuts and seeds, fruits, vegetables, and whole
grains. These compounds can trap free radicals and
reduce the levels of reactive oxygen molecules, thereby
protecting against tissue damage.35 Moreover, these sub-
stances may help inhibit plaque formation in the arteries
by reducing low- density lipoprotein oxidation, platelet ac-
tivation and aggregation, and inflammatory markers.36– 39
Experimental studies have also reported that a mixture of
compounds found in plant source foods had a synergistic
effect on enhancing antioxidant activity.40 ,41 Although the
mechanism remains to be established, our findings sup-
port a beneficial effect of a plant- centered diet on CVD
prevention at the general population level.
Study Strengths and Limitations
Because of the nature of the observational study de-
sign, we cannot rule out unmeasured or residual con-
founding. However, important potential confounding
factors were adjusted for regarding the association be-
tween diet and CVD. The results of this study may have
limited generalizability to other populations across dif-
ferent cultures, races/ethnicities, and periods of life.
Our study has several unique methodological fea-
tures that were used to evaluate the quality of plant-
centered diets. The CARDIA diet history questionnaire
measured comprehensively what specific foods were
eaten in the recent past, with an open- ended form. The
diet of the individuals with high APDQS score is cen-
tered on eating nutritionally rich plant foods, but with-
out excluding all animal products. Flexibility in dietary
choice may help maintain long- term stability in eating
healthfully. The APDQS allows choice by providing a
wide range of options in the way it is structured and
by emphasizing variety (46 groups). The components of
the APDQS were equally weighted with a maximum of
4 points, such that many food groups need to be part
of the diet to achieve a higher score. This is distinct from
other diet quality indices (eg, Healthy Eating Index- 2015
or Alternate Mediterranean Diet) that use a small num-
ber of food groups (≤13) within the scoring algorithm,
allowing a person to earn many points from single foods
and to avoid losing points for large consumption of less
healthy foods. Other strengths of this study include the
prospective design with the high retention rate during
a long follow- up, repeated measurements, and objec-
tively measured clinical data. Furthermore, the change
analysis allowed us to identify a clear temporality and
reduce the possibility of within- person confounding.
CONCLUSIONS
In summary, our study shows that long- term consump-
tion of a nutritionally rich plant- centered diet is associ-
ated with a lower risk of CVD. Furthermore, increased
plant- centered diet quality since young adulthood is as-
sociated with a lower subsequent risk of CVD through-
out middle age, independent of their earlier diet quality.
ARTICLE INFORMATION
Received December 30, 2020; accepted May 20, 2021.
Affiliations
Depar tment of Food Science and Nutrition ( Y.C., D.D.G.), University of
Minnes ota–Twin Cities, St Paul, M N; Division of Ep idemiolog y and Communi ty
Health (N.L., L.M.S., P.J.S., D.R.J.), and Cardiovascular Division, Department
of Medicine (D.A.D.), University of Minnesota– Twin Cities, Minneapolis, MN;
Division of Preventive Medicine, School of Medicine, University of Alabama
at Birmingham, Birmingham, AL (J.M.S.); Divisions of Cardi ology and
Research, Kaiser Permanente Northern California, Oakland, CA (J.S.R.); and
Depar tment of Medicine, University of California, San Francisco, CA (J.S.R.).
Acknowledgments
Author contributions: Drs Choi and Jacobs conceived and designed the
study. Dr Choi did the statistical analysis a nd drafted the manuscript. All
authors c ontributed to data interpretation and critical rev iew of the report.
Drs Choi, Shikany, and Schreiner obtained funding for this study. Dr Jacobs
supervised the study.
Sources of Funding
CARDIA is supported by contracts HHSN268201800003I, HHSN2682018
00004I, HHSN268201800005I, HHSN268201800006I, and HHSN268
201800007I from the National Heart, Lung, and Blood Institute (NHLBI),
Bethesda, Maryland. The sponsor, NHLBI has a representative on the Steering
Commit tee of CARDIA and par ticipated in study design, data collection, and
scientific review of this paper. The sponsor had no role in data analysis, data
interpretation, or writing of this repor t. Dr Choi is suppor ted by Graduate and
Professional Research Grant from the Healthy Food Healthy Lives Institute and
from the MnDRIVE Global Food Ventures Professional Development Program,
University of Minnesota, Minneapolis, Minnesota.
Disclosures
Dr Jacobs has been a paid consultant to the California Walnut C ommiss ion.
Dr Galla her is a paid member of the Nutrition Advisory Council for the
California Prune Board. Dr Steffen received a grant ending Febru ary 2020
with Dairy Management about dairy products. The remaining authors have
no disclosures to report.
Supplementary Material
Data S1
Tab l es S1 – S2
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SUPPLEMENTAL MATERIAL
Downloaded from http://ahajournals.org by on August 13, 2021
Data S1.
Supplemental Methods: Details of time-varying covariates in proportional hazards regression
Algebraically, suppose a covariate is called COV(t) (meaning that COV is repeatedly measured at CARDIA times t Y0, Y7 and Y20) and the time to
event variable is TIME, meaning time in study until event or censoring.
For the continuous covariates (total energy intake, physical activity level and BMI), we created a MEAN TO DATE function, that is, for each
variable, the covariate enters the regression as COV(1) for the time interval Y0-Y7, as mean[COV(1),COV(2)] for the time interval Y7-Y20, and as
mean[COV(1),COV(2),COV(3)] for the time interval Y20-Y32. We did this for each of the 3 continuous covariates.
For the disease status (hypertension, diabetes, and dyslipidemia), binary variables (0 or 1) was coded, with 0 meaning never diagnosed to date and 1
meaning ever diagnosed to date. For each variable, the diagnostic history covariate enters the model as COV (1) for the time interval Y0-Y7,
max[COV (1), COV (2)] for the time interval Y7-Y20, and max [COV (1), COV (2), COV (3)] for the time interval Y20-Y32. We did this for each of
the 3 binary covariates.
We used the SAS functions mean() and max(). These functions use whatever data are available. Thus if a person were missing COV(2), their value
in the interval Y0-Y7 would be COV(1), their value in the interval Y7-Y20 would also be COV(1) (because COV(2) is missing), and their value in
the interval Y20-Y32 would be mean[COV(1), COV(2), COV(3)].
Downloaded from http://ahajournals.org by on August 13, 2021
Table S1. Quintile cutpoints* of 46 individual food groups for total score computation of the APDQS and empirical examples of low (47) vs. high score
(81)†
Cutpoints (servings/day)
Low score
(APDQS=47 points)
High score
(APDQS=81 points)
Cutpoint 1
(20th
percentile)
Cutpoint 2
(40th
percentile)
Cutpoint 3
(60th
percentile)
Cutpoint 4
(80th
percentile)
Servings/day
Quintile
category
assigned
Score
Servings/day
Quintile
category
assigned
Score
Beneficially-rated
1. Fruit
0.3
0.71
1.23
2.18
0
1
0
0.81
3
2
2. Avocado
0
0.06
0.15
0.39
0
1
0
0
1
0
3. Beans and legumes
0
0.06
0.14
0.31
0.48
5
4
0.12
3
2
4. Green vegetables
0.01
0.10
0.23
0.53
0.44
4
3
0.08
2
1
5. Yellow vegetables
0
0.04
0.13
0.32
0
1
0
0
1
0
6. Tomato
0.14
0.26
0.42
0.71
1.27
5
4
0.99
5
4
7. Other vegetables
0.84
1.35
1.96
2.98
2.59
4
3
3.07
5
4
8. Nuts and seeds
0
0.14
0.46
1.10
0.03
2
1
0.75
4
3
9. Soy products
0
0.05
0.20
0.76
0
1
0
0
1
0
10. Whole grains
0.27
0.76
1.41
2.43
0.60
2
1
1.51
4
3
11. Vegetable oil
0.27
0.65
1.20
2.25
1.77
4
3
3.43
5
4
12. Fatty fish
0
0.10
0.15
0.29
0
1
0
0
1
0
13. Lean fish
0.02
0.22
0.49
1.05
0
1
0
0.33
3
2
14. Poultry
0.33
0.61
1.01
1.82
0.22
1
0
0.85
3
2
15. Beer
0
0.15
0.45
1.10
1.70
5
4
0.85
4
3
16. Wine
0
0.08
0.16
0.38
0
1
0
0
1
0
17. Liquor
0
0.08
0.20
0.45
0
1
0
0
1
0
18. Coffee
0
0.36
1.16
2.59
0
1
0
1.27
4
3
19. Tea
0
0.14
0.42
1.09
3.87
5
4
3.04
5
4
20.Low-fat
milk/Cheese/Yogurt
0.12
0.32
0.78
1.87
0.1
1
0
0.32
3
2
Neutrally-rated
1. Potatoes
0.07
0.17
0.32
0.62
0.22
3
0
0.94
5
0
2. Refined grains
1.90
3.03
4.42
6.52
3.81
3
0
2.15
2
0
3. Margarine
0.02
0.46
1.32
2.90
1.32
3
0
1.63
4
0
4. Chocolate
0
0.07
0.16
0.36
0
1
0
0
1
0
5. Meal replacements
0
0.10
0.26
0.56
0
1
0
0
1
0
6. Pickled foods
0
0.07
0.19
0.42
0.63
5
0
0.34
4
0
Downloaded from http://ahajournals.org by on August 13, 2021
7. Sugar substitutes
0
0.10
0.26
0.71
0
1
0
0.75
5
0
8. Lean red meats
0.02
0.29
0.61
1.24
0.22
2
0
1.20
4
0
9. Shellfish
0
0.06
0.16
0.38
0.19
4
0
0
1
0
10. Eggs
0
0.22
0.48
0.93
0.59
4
0
0.81
4
0
11. Soups
0
0.01
0.04
0.09
0
1
0
0
1
0
12. Diet soft drinks
0
0.28
0.83
1.62
0
1
0
1.52
4
0
13. Fruit juice
0.36
0.87
1.64
2.91
0
1
0
1.81
4
0
Adversely-rated
1. Fried potatoes
0
0.12
0.25
0.52
0.31
4
1
0.31
4
1
2. Grain desserts
0.11
0.29
0.55
1.05
0
1
4
0.51
3
2
3. Salty snacks
0
0.03
0.08
0.17
0.08
3
2
0
1
4
4. Pastries
0.20
0.46
0.83
1.49
3.70
5
0
0.35
2
3
5. Sweets
0.24
0.65
1.38
2.73
0.05
1
4
0.03
1
4
6. High-fat red meats
0.69
1.32
2.12
3.48
3.68
5
0
1.12
2
3
7. Processed meats
0.10
0.33
0.69
1.38
0.75
4
1
0.13
2
3
8. Organ meats
0
0.10
0.18
0.35
0.39
5
0
0
1
4
9. Fried poultry and
fish
0
0.02
0.08
1.15
0
1
4
0
1
4
10. Sauces
1.41
2.41
3.81
6.35
2.83
3
2
1.59
2
3
11. Soft drinks
0.12
0.57
1.30
2.45
5.80
5
0
0
1
4
12.Whole-fat
milk/Cheese/Yogurt
0.62
1.08
1.71
2.95
2.11
4
1
0.88
2
3
13. Butter
1.47
2.64
4.23
7.03
4.24
4
1
0.88
1
4
*The cutoffs of food group derived from the Y0 diet data was applied to follow-up data at Y7 and Y20 to track change in diet quality of individuals over time.
†To illustrate the scoring system, the two individuals were arbitrarily selected based on the median scores of the bottom and top quintiles of the Y0 data.
Downloaded from http://ahajournals.org by on August 13, 2021
Table S2. HR (95% CI) of incident CVD according to quintiles of the exam year-specific APDQS and for APDQS at a lagged
examination
Quintile 1
Quintile 2
Quintile 3
Quintile 4
Quintile 5
Each 1-SD
increment
(13 points)
P for
trend*
Y0 APDQS predicting CVD
over 32-years of follow-up
APDQS (median)
47
55
62
70
81
Unadjusted
cumulative
incidence % (n/N)
7.4 (76/1,026)
7.2 (72/999)
6.2 (61/984)
5.9 (58/991)
2.3 (22/946)
Model 1†
1 (ref)
0.92
(0.67–1.28)
0.85
(0.60–1.20)
0.92
(0.64–1.33)
0.44
(0.26–0.75)
0.80
(0.69–0.93)
0.003
Model 2‡
1 (ref)
0.92
(0.66–1.27)
0.85
(0.60–1.20)
0.99
(0.69–1.43)
0.50
(0.29–0.84)
0.83
(0.71–0.97)
0.016
5-year lag, after Y5
1 (ref)
0.91
(0.66–1.27)
0.84
(0.59–1.19)
0.96
(0.67–1.39)
0.49
(0.29–0.83)
0.82
(0.70–0.96)
0.012
Y7 APDQS predicting CVD
over 25-years of follow-up,
after Y7
APDQS (median)
51
60
67
74
83
Unadjusted
cumulative
incidence % (n/N)
7.2 (52/722)
8.0 (67/839)
5.0 (38/755)
4.1 (28/686)
2.8 (22/797)
Model 1†
1 (ref)
1.19
(0.83–1.72)
0.80
(0.52–1.23)
0.74
(0.46–1.20)
0.59
(0.34–1.02)
0.84
(0.71–0.99)
0.041
Model 2‡
1 (ref)
1.16
(0.81–1.68)
0.85
(0.55–1.31)
0.77
(0.48–1.26)
0.66
(0.38–1.15)
0.87
(0.73–1.04)
0.14
8-year lag, after Y15
1 (ref)
1.05
(0.70–1.58)
0.88
(0.55–1.41)
0.82
(0.48–1.39)
0.59
(0.31–1.10)
0.87
(0.72–1.06)
0.16
Downloaded from http://ahajournals.org by on August 13, 2021
Y20 APDQS predicting CVD
over 12-years of follow-up,
after Y20
APDQS (median)
54
64
70
78
88
Unadjusted
cumulative
incidence % (n/N)
6.4 (40/626)
4.7 (29/619)
3.7 (20/538)
2.7 (18/666)
1.7 (10/576)
Model 1†
1 (ref)
0.85
(0.52–1.37)
0.73
(0.42–1.26)
0.57
(0.32–1.04)
0.42
(0.20–0.88)
0.71
(0.57–0.87)
0.001
Model 2‡
1 (ref)
0.89
(0.55–1.44)
0.86
(0.49–1.50)
0.72
(0.39–1.31)
0.59
(0.27–1.28)
0.79
(0.63–0.99)
0.041
5-year lag, after Y25
1 (ref)
0.82
(0.45–1.52)
0.81
(0.40–1.62)
0.68
(0.32–1.43)
0.57
(0.22–1.45)
0.79
(0.60–1.04)
0.10
APDQS = A Priori Diet Quality Score; CI = confidence interval; HR = hazard ratio.
Note: Each APDQS variable measured in a different exam year was set at the baseline.
*Statistical significance was estimated by modeling APDQS as a continuous variable in the model.
†Model 1: Baseline age (continuous), sex, race (White and Black), baseline total energy intake (continuous), and maximal educational
attainment (continuous).
‡Model 2: Model 1 + parental history of CVD (yes vs no), baseline smoking status (never, former, and current), and baseline physical activity
level (continuous).
Downloaded from http://ahajournals.org by on August 13, 2021
