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Adolescent and mid-life diet: risk of colorectal cancer in the NIH-AARP
Diet and Health Study
1–3
Elizabeth H Ruder, Anne CM Thie
´baut, Frances E Thompson, Nancy Potischman, Amy F Subar, Yikyung Park,
Barry I Graubard, Albert R Hollenbeck, and Amanda J Cross
ABSTRACT
Background: Colorectal cancer has a natural history of several
decades; therefore, the diet consumed decades before diagnosis
may aid in understanding this malignancy.
Objective: The objective was to investigate diet during adolescence
and 10 y before baseline (ages 40–61 y) in relation to colorectal
cancer.
Design: Participants in the NIH-AARP Diet and Health Study (n=
292,797) completed a 124-item food-frequency questionnaire (FFQ)
about diet in the past 12 mo and two 37-item FFQs about diet at
ages 12–13 y and 10 y previously. Cox regression was used to
estimate multivariate HRs and 95% CIs for colon (n= 2794) and
rectal (n= 979) cancers within quintiles of exposures.
Results: Colon cancer risk was lower in the highest than in the
lowest quintile of vitamin A (HR: 0.82; 95% CI: 0.72, 0.92) and
vegetable (HR: 0.81, 0.70, 0.92) intakes during adolescence. Those
in the highest intake category 10 y previously for calcium (HR:
0.83; 95% CI: 0.73, 0.94), vitamin A (HR: 0.81; 95% CI: 0.71,
0.92), vitamin C (HR: 0.83; 95% CI: 0.72, 0.95), fruit (HR: 0.84;
95% CI: 0.73, 0.97), and milk (HR: 0.78; 95% CI: 0.67, 0.90) had
a lower risk of colon cancer, but a higher risk was observed for total
fat (HR: 1.15; 95% CI: 1.01, 1.30), red meat (HR: 1.31; 95% CI:
1.12, 1.53), and processed meat (HR: 1.24; 95% CI: 1.06, 1.45). For
rectal cancer, milk was inversely associated (HR: 0.75; 95% CI:
0.58, 0.96) with risk.
Conclusion: Adolescent and midlife diet may play a role in co-
lorectal carcinogenesis. Am J Clin Nutr 2011;94:1607–19.
INTRODUCTION
Colorectal cancer is the third most common cancer worldwide;
thus strategies for prevention are of critical public health im-
portance (1). Despite the predominating belief that diet plays an
important role in the development of colorectal cancer, the lit-
erature has been largely inconclusive (2). However, the vast
majority of epidemiologic research has investigated diets con-
sumed within ;10 y of diagnosis, with little research refer-
encing diet earlier in life. Colorectal cancer is a multistep
process with a natural history of several decades (3, 4); there-
fore, it is reasonable to hypothesize that diet earlier in life, rather
than recent adult diet, may be informative in understanding this
malignancy. A growing body of literature has documented
a potential role for adolescent diet in the development of breast
cancer, independent of diet consumed in recent adult life (5–7).
Limited work has investigated early life (eg, childhood or ado-
lescence), or mid-life (;40–60 y of age) exposures in relation to
colorectal carcinogenesis, although the available evidence sug-
gests that transient caloric restriction in adolescence is associ-
ated with a lower risk of colorectal cancer after age 55 y (8).
Furthermore, caloric restriction in adolescence or early adult-
hood is associated with a lower risk of developing a colorectal
tumor characterized by the CpG island methylator phenotype
(9), which suggests that adolescence or early adulthood may be
a period susceptible to epigenetic modification. Only 2 epide-
miologic studies have investigated early-life dietary exposures
in relation to colorectal cancer, both of which were restricted to
milk or dairy consumption and had mixed results (10, 11). In-
takes of nutrients and specific food groups potentially influence
the natural history of carcinogenesis; however, unlike severe
caloric restriction, they provide a potentially achievable avenue
for preventive dietary behavior. In this investigation, we used
data from the NIH-AARP Diet and Health Study—a large
prospective cohort—to examine the association between in-
take of nutrients and food groups at ages 12–13 y, diet 10 y
before baseline, and risk of adenocarcinoma in the colon and
rectum.
SUBJECTS AND METHODS
Study population
The NIH-AARP Diet and Health Study is a prospective cohort
of men and women aged 50–71 y at recruitment from 6 US states
(California, Florida, Louisiana, New Jersey, North Carolina, and
1
From the Division of Cancer Epidemiology and Genetics, National Can-
cer Institute, NIH, Department of Health and Human Services, Rockville,
MD (EHR, YP, BIG, and AJC); the Cancer Prevention Fellowship Program,
Center for Cancer Training, National Cancer Institute, NIH, Department of
Health and Human Services, Rockville, MD (EHR); INSERM, U657, Paris,
France (ACMT); Applied Research Program, Division of Cancer Control and
Population Sciences, National Cancer Institute, Rockville, MD (FET, NP,
and AFS); and AARP, Washington, DC (ARH).
2
Supported in part by the Intramural Research Program of the National
Cancer Institute, NIH, Department of Health and Human Services.
3
Address correspondence to EH Ruder, 6120 Executive Boulevard, Rock-
ville, MD, 20852. E-mail: rudereh@mail.nih.gov.
Received June 6, 2011. Accepted for publication September 13, 2011.
First published online November 9, 2011; doi: 10.3945/ajcn.111.020701.
Am J Clin Nutr 2011;94:1607–19. Printed in USA. Ó2011 American Society for Nutrition 1607
Pennsylvania) and 2 metropolitan areas (Atlanta, GA, and
Detroit, MI). The study was described in detail previously (12). A
self-administered baseline questionnaire regarding demographic
and lifestyle characteristics, including diet in the previous 12 mo,
was completed in 1995–1996 by a total of 617,119 individuals. A
second questionnaire, hereafter called the risk factor question-
naire, was mailed to participants ;6 months after completion of
the baseline questionnaire; this questionnaire included abbrevi-
ated assessments of usual dietary intake 10 y previously (when
participants were ;40–61 y of age) and diet at ages 12–13 y.
The risk factor questionnaire was returned by 334,907 in-
dividuals. For our analyses, we excluded individuals for whom
either the baseline (n= 6959) or the risk factor questionnaire
(n= 3424) was completed by proxy respondents, those with
prevalent cancer at the administration of the baseline (n=
14,565) or risk factor (n= 4297) questionnaire, those who had
a death only report for any cancer (n= 983), those with 0 person-
years of follow-up (n= 19), and those in the extremes of energy
intake (defined as more than twice the interquartile range of
the Box-Cox logarithmic-transformed scale) for either diet in
the previous 12 mo (n= 2334) or during ages 12–13 y (n=
595). The resulting cohort for our analysis included 292,797
participants (171,171 men and 121,626 women). The NIH-
AARP Diet and Health Study was approved by the Special
Studies Institutional Review Board of the US National Cancer
Institute.
Cohort follow-up and case ascertainment
Cohort members were followed for change of address by using
the US Postal Service. Periodic linkage of the cohort to the US
Social Security Administration Death Master File, follow-up
searches of the National Death Index, cancer registry linkage,
questionnaire responses, and responses to other mailings were
used to obtain vital status. We identified cancer cases through
probabilistic linkage with state cancer registries. Our cancer
registry ascertainment area was expanded beyond the 8 original
states from which the cohort was recruited to include Texas and
Arizona, where participants most commonly relocated to
during follow-up. Approximately 5% of participants were lost
to follow-up as a result of moving out of the 10 states. Our case
ascertainment method, described elsewhere, indicates that
;90% of cancers were identified through the cancer registries
(13).
Colorectal cancer endpoints were defined by anatomic site and
histologic code of the International Classification of Diseases for
Oncology (14) and included codes C180-C189, C199, C209, and
C260. We further classified cases as those in the colon (C180-189,
C260) or rectum (C199, C209). We only included first primary
diagnoses of adenocarcinoma; we excluded cases with un-
specified histologies (n= 25), neuroendocrine tumors/carcinoids
(n= 82), lymphomas (n= 25), sarcomas (n= 8), squamous cell
carcinomas (n=8), large cell carcinoma with rhabdoid phe-
notype (n= 1), cloacogenic carcinoma (n= 1), gastrinoma (n=
1), cribriform carcinoma (n= 1), and pigmented nevus (n= 2).
Follow-up for these analyses began on the date the risk factor
questionnaire was received and continued until censoring at the
end of 2006 or when the participant moved out of the 10 state
cancer registry areas, had a cancer diagnosis, or died, whichever
came first.
Dietary assessment
Approximately 6 mo after the baseline questionnaire was
completed, participants were asked to complete the risk factor
questionnaire. This questionnaire included two 37-item food-
frequency questionnaires (FFQs): one referencing diet during
12–13 y of age and the other referencing diet 10 y previously.
Both 37-item FFQs began with introductory questions to help
respondents focus on the time period of interest (15, 16); for
example, for diet 10 y previously, the introductory statement in
the questionnaire read as follows: “To help you focus on that
period of time, this was during President Reagan’s second term in
office, and the following landmark events took place: the space
shuttle Challenger disaster, the Iran-Contra hearing, and the Wall
Street stock market crash.” In addition, both 37-item FFQs asked
questions to help participants focus on the time period of interest,
such as “what year was it?,” “where were you living (city and
street)?,” “with whom were you living?,” “what school grade
were you in?” (FFQ for 12-13 y of age, only), and “were you
working outside the home?” (only for FFQ for 10 y previously).
The 37-food items included in the FFQ were selected because of
their major contribution to sources of fat, vitamin A, and vitamin
C, which at the time of FFQ development were the nutrients
hypothesized to be of most interest in carcinogenesis; in addition
to these nutrients, period-relevant databases allowed us to
evaluate energy, carbohydrate, protein, and calcium. Participants
were asked to select from 9 categories of frequency of con-
sumption, ranging from “never” to “2 or more times per day.”
Portion size was not ascertained in the 37-item FFQs, but was
estimated by assigning the median sex-specific portion size from
US Federal government food and nutrition surveys consistent
with the time period being queried. For the FFQ referencing diet
during 12–13 y of age, data from boys and girls aged 12–13 y who
completed the US Department of Agriculture 1965–1966
Household Food Consumption Survey (HFCS)—the first na-
tionwide food consumption survey of individuals—were used to
assign portion size. The HFCS was also used to determine energy
and nutrient values (with the exception of fiber) per 100-g
serving. The HFCS did not include values for fiber. Fiber values
from the NHANES 1999–2000 database were attributed to all 3
survey periods. The energy or nutrient values per 100-g serving
were multiplied by the median sex-specific serving size and
multiplied again by the midpoint value per day for each frequency
category, with the exception of the open-ended highest category
(“2 or more times per day”), for which we used median frequency
of consumption among boys and girls in the 1965 HFCS who
reported consuming that specific item 2 times/d. A similar
method was used for the 37-item FFQ referencing diet 10 y
before baseline; only portion sizes and energy/nutrient (carbo-
hydrate, total fat protein, calcium, vitamins A and C) intakes
were based on NHANES-III (17). In addition, participants
completed a 124-item FFQ pertaining to diet in the previous 12
mo (referred to as recent adult diet) as part of the 1995–1996
baseline questionnaire. This FFQ was based on the National
Cancer Institute’s Diet History Questionnaire; participants were
asked to select from 10 categories of frequency of consumption,
ranging from “never” to “6+ times per day” and from 1 of 3
possible portion sizes. Data were linked with the 1994–1996 US
Department of Agriculture’s Continuing Survey of Food Intakes
by Individuals to ascertain energy and nutrient intakes (18).
1608 RUDER ET AL
To investigate food groups from the 124-item FFQ of diet in
the previous 12 mo, we calculated variables based on the US
Department of Agriculture’s MyPyramid Equivalents Database
(19). Data for the 37-item FFQs were insufficient to calculate the
MyPyramid Equivalents Database; thus, we defined food groups
(grains, vegetables, fruit, milk, red meat, processed meat, solid
fat, and sweet baked goods) and calculated food group values as
the sum of the frequency of intake for each food item within the
food group.
Statistical analysis
The HRs and 95% CIs were estimated by using Cox pro-
portional hazards regression, with person-years as the underlying
time metric; analyses that used age as the underlying time metric
yielded nearly identical HRs. The proportional hazard assump-
tion was verified by using a time interaction model. For the main
analyses, participants were categorized into quintiles of intake
(with one exception), and the lowest quintile of intake was used as
the reference group. The exception to the formation of quintiles
occurred in the analysis of milk consumption during ages 12–13
y. For this analysis, .50% of the study population consumed
milk either “1 time per day” or “2 or more times per day.”
Because of the large number of intake frequencies clustered at
these values, it was impossible to create nearly evenly populated
quintiles of intake. Thus, for milk consumption at 12–13 y of
age, we created 5 categories of intake defined respectively as
follows: “never” to “1–11 times per year” (7%), “1–3 times per
month” to “3–4 times per week” (21%), “5–6 times per week”
(15%), “1 time per day” (22%), and “2 or more times per day”
(35%). Tests for trend were calculated by assigning a median
value for each quintile of consumption or, in the case of ado-
lescent milk consumption, an ordinal variable for the category of
consumption. Spearman correlation coefficients between quin-
tile/category of intake during 12–13 y of age and in the 12 mo
before baseline as well as between diet 10 y before baseline and
diet in the previous 12 mo were calculated to evaluate the
similarity of dietary exposures over time.
To examine changes in consumption patterns over time, we
divided participants into tertiles of nutrient or food group intake
at 2 time points: adolescence and recent adulthood, defined as the
12 mo before baseline. Individuals who were in the lowest
category of consumption at both time points were the referent
group, and comparisons were made to individuals who were in
the highest consumption group as adolescents but were in the
lowest category as adults, individuals who were in the lowest
category as adolescents but were in the highest category as adults,
individuals who remained in the middle tertile for both time
points or whose tertile placement changed by only one category
from adolescence to adulthood, and individuals who were in the
highest consumption group as adolescents and as adults. To
maximize clarity, we present results only for individuals in the
extreme tertiles of intake and do not present results from the
group of individuals who remained in the middle tertile for both
time points or whose tertile placement changed by only one
category from adolescence to adulthood.
The final multivariate models contained only variables that
changed the HR by 10% or were established risk factors for
colorectal cancer. These variables included age, BMI, energy
intake, smoking, physical activity, and use of nonsteroidal an-
tiinflammatory drugs at the time of the risk factor questionnaire,
alcohol consumption at study baseline, sex, race, education, and
self-report of a first-degree relative with a history of colon
cancer. Variables that were evaluated but did not alter the HR by
10% or more included personal history of diabetes or co-
lorectal polyps, being 12–13 y of age during 1942–1946 (a pe-
riod of food rationing in the United States), colorectal cancer
screening practices, stage at diagnosis, age at menarche, or BMI
at age 18 y. Data on father’s occupation were available for
179,202 individuals, but inclusion of this variable in analyses of
this subset of individuals did not materially alter the HRs.
To test for heterogeneity between the anatomic subsites (colon
compared with rectum and proximal colon compared with distal
colon), we calculated the weighted average of the 2 bcoefficients
from the Cox model, with weights being proportional to the
inverse of the variances. We then calculated the following chi-
square statistic with one df:
T¼X2
i¼1ð
^
bi
bÞ2=r2
ið1Þ
wherein
^
biand r2
iare the coefficient and its variance for each
subsite and
bis the weighted average of the bcoefficients. In
addition, we conducted sensitivity analyses to examine the po-
tential effects of preclinical disease on baseline diet by exclud-
ing the first 2 y of follow-up, and we stratified our analyses by
sex. All statistical analyses were carried out by using Statistical
Analytic Systems software version 9.1 (SAS Institute Inc).
RESULTS
A total of 3773 cases of colorectal cancer (2480 in men and
1293 in women) were identified among the 292,797 eligible
participants; of these, 2794 were located in the colon and 979
were in the rectum. Tests for heterogeneity did not indicate
significant differences between proximal compared with distal
colon tumors; therefore, results are presented only for colon and
rectal cancer.
The study participants were predominately white (92.8%), and
58.5% were men. The mean age at administration of the risk
factor questionnaire was 62.8 y. Those with cancer tended to be
older, to consume more calories and alcohol, to be less educated,
to be less physically active, and to not take nonsteroidal anti-
inflammatory drugs or hormone replacements as often as those
without cancer (Table 1). Spearman correlation coefficients for
adolescent and recent adult diet ranged from 0.09 for fat and
protein to 0.30 for vegetables (see Supplemental Table 1 under
“Supplemental data” in the online issue). Correlations among
diet 10 y before baseline and recent adult diet were higher and
ranged from 0.23 for protein to 0.54 for milk (see Supplemental
Table 2 under “Supplemental data” in the online issue).
Consumption of specific macronutrients (carbohydrate, total
fat, or protein) during ages 12–13 y of age was not associated with
either colon or rectal cancer, although a greater risk of rectal
cancer was observed among individuals in the highest compared
with the lowest quintile of fiber intake (Table 2). Individuals in
the highest, compared with the lowest, quintile of calcium (HR:
0.85; 95% CI: 0.75, 0.95; P-trend = 0.03) and those in the
highest quintile of vitamin A during ages 12–13 y (HR = 0.80;
95% CI: 0.71, 0.90; P-trend ,0.01) had a lower risk of colon
cancer; although the association for calcium was attenuated after
ADOLESCENT AND MID-LIFE DIET AND COLORECTAL CANCER 1609
adjustment for adult intake (Table 2). No statistically significant
associations were detected for calcium or vitamin A and rectal
cancer or between vitamin C consumption and colon or rectal
cancer. Tests for heterogeneity were significant only for the
association of vitamin A and colon compared with rectal cancer
(P-heterogeneity ,0.01).
Examination of food groups consumed during ages 12–13 y
showed a statistically significant reduction in colon cancer among
individuals with high consumption of vegetables, and this as-
sociation persisted after adjustment for recent adult vegetable
intake (quintile 5 compared with quintile 1: HR = 0.81; 95% CI:
0.70, 0.92; P-trend = 0.01; Table 3). High milk consumption
was also associated with a lower colon cancer risk, but this
association was attenuated after adjustment for adult milk con-
sumption. No associations were found between intake of any of
the food groups examined at 12–13 y of age and rectal cancer
(Table 3), and the test for heterogeneity of the association of
vegetable intake with colon compared with rectal cancer was
statistically significant (P-heterogeneity = 0.03).
Investigation of diet 10 y before baseline, when participants
were 40–61 y of age, showed a greater number of statistically
significant associations with colon and rectal cancer than did diet
at ages 12–13 y. After adjustment for recent adult diet, a statis-
tically significant positive association between total fat con-
sumption 10 y before baseline was detected for colon cancer
(quintile 5 compared with quintile 1: HR= 1.15; 95% CI: 1.01,
1.30; P-trend = 0.02), but not for rectal cancer (Table 4), al-
though the test for heterogeneity indicated that the risks were
not statistically different (P-heterogeneity = 0.31). After ad-
justment for adult diet, no significant associations were detected
for intake of carbohydrate or protein with colon or rectal cancer,
although a borderline significant positive association between
fiber and rectal cancer was observed (quintile 5 compared with
quintile 1: HR: 1.26; 95% CI: 1.00, 1.58; P-trend = 0.06), but
not for colon cancer (P-heterogeneity = 0.05). A lower risk of
colon cancer was found for individuals in the highest quintile of
calcium (HR: 0.83; 95% CI: 0.73; 0.94; P-trend ,0.01), vita-
min A (HR: 0.81; 95% CI: 0.71, 0.92; P-trend = 0.03), and
vitamin C (HR: 0.83; 95% CI: 0.72; 0.95, P-trend = 0.02) in the
10 y before baseline, and these associations remained after ad-
justment for recent adult diet; no associations were observed
between these 3 nutrients and rectal cancer. A food group–based
analysis of diet 10 y before baseline adjusted for recent adult
consumption showed a statistically significant lower risk of
colon cancer for those in the highest category of fruit (HR: 0.84;
95% CI: 0.73, 0.97; P-trend = 0.02) or milk (HR: 0.78; 95% CI:
0.67, 0.90; P-trend ,0.01), and a greater risk for those in the
highest quintile of red meat intake (HR: 1.31; 95% CI: 1.12,
1.53; P-trend ,0.01) and processed meat (HR: 1.24; 95% CI:
1.06, 1.45; P-trend ,0.01) (Tab le 5 ). A reduced risk of rectal
cancer was observed among individuals in the highest cate-
gory of milk intake 10 y before baseline (HR: 0.75; 95% CI:
0.58, 0.96; P-trend = 0.05), whereas those in the highest
quintile of grains had a borderline significantly greater rectal
cancer risk, although the trend was not statistically signifi-
cant (HR: 1.28; 95% CI: 1.00; 1.64, P-trend = 0.12). Tests for
heterogeneity for the association between food groups
and colon or rectal cancer were significant only for fruit (P-
heterogeneity ,0.01).
Results excluding cases accrued in the first 2 y of follow-up
were not materially different from the overall study population.
We found no significant interactions by sex, except for dietary
fiber and colon cancer for adolescent diet (P,0.001) and diet
10 y before baseline (P,0.001). Stratified analyses of fiber
TABLE 1
Distribution of covariates in the NIH-AARP Diet and Health Study (n= 292,797)
Cohort
(n= 292,797)
Colon cancer
(n= 2794)
Rectal cancer
(n= 979)
Age (y) 62.8 65.3
1
64.7 64.7 64.2 64.9
Sex, male [n(%)] 171,171 (58.5) 1799 (64.4) 681 (70.0)
Married [n(%)] 200,327 (68.4) 1933 (69.2) 700 (71.5)
First-degree relative with colon cancer [n(%)] 26,367 (9.0) 290 (10.4) 72 (7.4)
BMI at baseline (kg/m
2
) 26.9 (5.0) 27.4 (5.0) 27.3 (5.1)
Physically active at baseline, 5 times/wk [n(%)] 58,862 (20.1) 527 (18.9) 185 (18.9)
Use of aspirin in previous 12 mo [n(%)] 212,604 (73.3) 1991 (72.3) 690 (71.0)
Use of ibuprofen in previous 12 mo [n(%)] 163,660 (56.6) 1354 (49.1) 486 (50.2)
Use of hormone replacement therapy, ever [n(%)]
2
66,698 (54.8) 426 (42.8) 133 (44.6)
College graduate [n(%)] 121,503 (41.5) 1055 (37.8) 325 (33.2)
Race [n(%)]
White 271,813 (92.8) 2602 (93.1) 915 (93.5)
Black 9194 (3.1) 84 (3.0) 20 (2.0)
Other
3
11,790 (4.0) 108 (3.9) 44 (4.5)
Tobacco smoking [n(%)]
Never 105,305 (36.0) 884 (31.7) 265 (27.1)
Former 141,436 (48.3) 1,489 (53.3) 546 (55.8)
Current 36,699 (12.5) 334 (11.9) 127 (13.0)
Total energy (kcal/d) 1819 6771 1870 6819 1933 6842
Alcohol intake at baseline (g/d) 12.4 630.9 14.8 635.7 18.0 642.0
1
Mean 6SD (all such values).
2
Among females only.
3
Includes Hispanic, Asian, Pacific-Islander, American Indian, Alaskan Native, and unknown.
1610 RUDER ET AL
TABLE 2
Multivariate risks for the association between intakes of energy and nutrients at ages 12–13 y and colorectal cancer in the NIH-AARP Diet and Health Study
(n= 292,797)
Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5 P-trend
1
Carbohydrate
Median (g/1000 kcal) 71 81 88 96 109 —
Colon cancer (no. of cases) 534 526 535 591 608 —
Rectal cancer (no. of cases) 188 205 209 180 197 —
Colon
2
1.00 0.98 (0.87, 1.11)
3
0.99 (0.87, 1.12) 1.06 (0.94, 1.19) 1.04 (0.92, 1.17) 0.30
Colon + recent adult intake
4
1.00 0.99 (0.88, 1.12) 1.01 (0.89, 1.14) 1.08 (0.96, 1.22) 1.07 (0.95, 1.21) 0.13
Rectal
2
1.00 1.10 (0.90, 1.35) 1.13 (0.93, 1.38) 0.98 (0.79, 1.20) 1.03 (0.84, 1.27) 0.84
Rectal + recent adult intake
4
1.00 1.11 (0.91, 1.36) 1.15 (0.94, 1.40) 1.00 (0.81, 1.23) 1.07 (0.87, 1.32) 0.82
Total fat
Median (g/1000 kcal) 46 51 54 57 61 —
Colon cancer (no. of cases) 596 587 527 540 544 —
Rectal cancer (no. of cases) 182 192 190 211 204 —
Colon
2
1.00 1.02 (0.91, 1.14) 0.93 (0.82, 1.05) 0.95 (0.84, 1.07) 0.95 (0.84, 1.07) 0.22
Colon + recent adult intake
4
1.00 1.01 (0.90, 1.14) 0.92 (0.81, 1.03) 0.94 (0.83, 1.06) 0.93 (0.82, 1.05) 0.12
Rectal
2
1.00 1.09 (0.88, 1.33) 1.04 (0.84, 1.28) 1.14 (0.93, 1.40) 1.05 (0.85, 1.29) 0.57
Rectal + recent adult intake
4
1.00 1.07 (0.87, 1.32) 1.02 (0.83, 1.26) 1.11 (0.91, 1.37) 1.02 (0.83, 1.26) 0.74
Protein
Median (g/1000 kcal) 35 39 41 43 47 —
Colon cancer (no. of cases) 577 582 565 540 530 —
Rectal cancer (no. of cases) 206 184 183 213 193 —
Colon
2
1.00 1.05 (0.93, 1.18) 1.04 (0.93, 1.17) 1.01 (0.90, 1.14) 1.00 (0.89, 1.13) 0.82
Colon + recent adult intake
4
1.00 1.06 (0.94, 1.19) 1.05 (0.93, 1.18) 1.02 (0.90, 1.15) 1.01 (0.90, 1.14) 0.93
Rectal
2
1.00 0.93 (0.76, 1.14) 0.92 (0.75, 1.13) 1.11 (0.92, 1.35) 1.00 (0.82, 1.23) 0.50
Rectal + recent adult intake
4
1.00 0.91 (0.74, 1.11) 0.91 (0.74, 1.11) 1.10 (0.91, 1.33) 0.99 (0.81, 1.22) 0.58
Fiber
Median (g/1000 kcal) 4.5 5.8 6.9 8.2 10.8 —
Colon cancer (no. of cases) 521 561 534 570 608 —
Rectal cancer (no. of cases) 154 182 223 207 213 —
Colon
2
1.00 1.05 (0.93, 1.18) 0.95 (0.85, 1.08) 0.99 (0.88, 1.12) 1.02 (0.90, 1.15) 0.99
Colon + recent adult intake
4
1.00 1.06 (0.94, 1.20) 0.97 (0.86, 1.10) 1.01 (0.90, 1.15) 1.05 (0.93, 1.19) 0.61
Rectal
2
1.00 1.16 (0.93, 1.44) 1.38 (1.12, 1.70) 1.24 (1.00, 1.53) 1.27 (1.03, 1.57) 0.06
Rectal + recent adult intake
4
1.00 1.16 (0.94, 1.44) 1.39 (1.13, 1.72) 1.25 (1.01, 1.55) 1.29 (1.04, 1.60) 0.04
Calcium
Median (mg/1000 kcal) 262 356 442 582 746 —
Colon cancer (no. of cases) 632 546 547 553 516 —
Rectal cancer (no. of cases) 217 197 200 179 186 —
Colon
2
1.00 0.87 (0.77, 0.98) 0.87 (0.77, 0.97) 0.88 (0.79, 0.99) 0.85 (0.75, 0.95) 0.03
Colon + recent adult intake
4
1.00 0.88 (0.79, 1.00) 0.90 (0.80, 1.01) 0.93 (0.83, 1.04) 0.90 (0.80, 1.02) 0.28
Rectal
2
1.00 0.90 (0.74, 1.10) 0.92 (0.76, 1.12) 0.86 (0.71, 1.05) 0.92 (0.75, 1.12) 0.37
Rectal + recent adult intake
4
1.00 0.92 (0.75, 1.11) 0.94 (0.77, 1.15) 0.88 (0.72, 1.08) 0.95 (0.78, 1.16) 0.59
Vitamin A
Median (IU/1000 kcal) 1556 2012 2404 2897 3992 —
Colon cancer (no. of cases) 606 569 515 578 526 —
Rectal cancer (no. of cases) 174 193 199 211 202 —
Colon
2
1.00 0.92 (0.82, 1.03) 0.82 (0.73, 0.93) 0.91 (0.81, 1.02) 0.80 (0.71, 0.90) ,0.01
Colon + recent adult intake
4
1.00 0.93 (0.82, 1.04) 0.83 (0.74, 0.94) 0.93 (0.83, 1.04) 0.82 (0.72, 0.92) ,0.01
Rectal
2
1.00 1.13 (0.92, 1.39) 1.15 (0.94, 1.41) 1.23 (1.01, 1.51) 1.16 (0.95, 1.43) 0.18
Rectal + recent adult intake
4
1.00 1.13 (0.92, 1.39) 1.16 (0.94, 1.42) 1.25 (1.01, 1.53) 1.19 (0.96, 1.47) 0.12
Vitamin C
Median (mg/1000 kcal) 17 25 36 54 84 —
Colon cancer (no. of cases) 616 564 551 531 532 —
Rectal cancer (no. of cases) 193 224 205 197 160 —
Colon
2
1.00 0.91 (0.82, 1.03) 0.92 (0.82, 1.03) 0.93 (0.83, 1.05) 0.93 (0.83, 1.05) 0.46
Colon + recent adult intake
4
1.00 0.92 (0.82, 1.04) 0.94 (0.84, 1.06) 0.95 (0.85, 1.07) 0.96 (0.85, 1.08) 0.85
Rectal
2
1.00 1.17 (0.96, 1.42) 1.11 (0.91, 1.35) 1.11 (0.90, 1.35) 0.93 (0.75, 1.15) 0.19
Rectal + recent adult intake
4
1.00 1.18 (0.97, 1.43) 1.11 (0.91, 1.36) 1.13 (0.92, 1.39) 0.96 (0.77, 1.19) 0.34
1
Linear test for trend derived by using the median value of each quintile.
2
Adjusted for energy at ages 12–13 y, age at completion of risk-factor questionnaire, sex, BMI, race, education, physical activity, alcohol consumption,
smoking, use of nonsteroidal antiinflammatory drugs, use of hormone replacement therapy, and self-report of a first-degree relative with a history of colon cancer.
3
HR; 95% CI in parentheses (all such values); calculated by Cox proportional hazard regression models.
4
Adjusted for energy at ages 12–13 y, energy in recent adulthood, nutrient of interest in recent adulthood, age at completion of risk-factor questionnaire,
sex, BMI, race, education, physical activity, alcohol consumption, smoking, use of nonsteroidal antiinflammatory drugs, use of hormone replacement therapy,
and self-report of a first-degree relative with a history of colon cancer.
ADOLESCENT AND MID-LIFE DIET AND COLORECTAL CANCER 1611
TABLE 3
Multivariate risks for the association between food group intake at ages 12–13 y and colorectal cancer in older adulthood in the NIH-AARP Diet and Health
Study (n= 292,797)
Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5 P-trend
1
Grains
2
Median (times consumed/d) 0.30 0.79 1.00 1.07 2.02 —
Colon cancer (no. of cases) 565 536 478 513 702 —
Rectal cancer (no. of cases) 208 222 150 180 219 —
Colon
3
1.00 0.99 (0.86, 1.10)
4
1.03 (0.91, 1.17) 1.04 (0.91, 1.18) 1.09 (0.96, 1.25) 0.10
Colon + recent adult intake
5
1.00 0.99 (0.87, 1.12) 1.05 (0.92, 1.19) 1.05 (0.92, 1.20) 1.11 (0.98, 1.27) 0.07
Rectal
3
1.00 1.02 (0.84, 1.24) 0.82 (0.66, 1.02) 0.88 (0.70, 1.09) 0.82 (0.66, 1.03) 0.07
Rectal + recent adult intake
5
1.00 1.02 (0.84, 1.24) 0.82 (0.66, 1.02) 0.89 (0.71, 1.10) 0.84 (0.67, 1.05) 0.10
Vegetables
6
Median (times consumed/d) 0.39 0.82 1.20 1.66 2.57 —
Colon cancer (no. of cases) 662 529 548 563 492 —
Rectal cancer (no. of cases) 191 210 189 215 174 —
Colon
3
1.00 0.84 (0.75, 0.94) 0.86 (0.76, 0.97) 0.87 (0.77, 0.98) 0.80 (0.70, 0.91) 0.01
Colon + recent adult intake
5
1.00 0.85 (0.75, 0.95) 0.87 (0.77, 0.98) 0.88 (0.78, 1.00) 0.81 (0.70, 0.92) 0.01
Rectal
3
1.00 1.21 (0.99, 1.47) 1.08 (0.88, 1.34) 1.26 (1.02, 1.55) 1.10 (0.87, 1.39) 0.52
Rectal + recent adult intake
5
1.00 1.19 (0.98, 1.46) 1.07 (0.86, 1.32) 1.23 (1.00, 1.53) 1.07 (0.84, 1.36) 0.72
Fruit
7
Median (times consumed/d) 0.11 0.41 0.80 1.28 2.07 —
Colon cancer (no. of cases) 614 627 537 513 504 —
Rectal cancer (no. of cases) 212 229 180 197 161 —
Colon
3
1.00 0.99 (0.89, 1.11) 0.99 (0.88, 1.11) 0.99 (0.88, 1.12) 0.94 (0.82, 1.08) 0.36
Colon + recent adult intake
5
1.00 1.01 (0.90, 1.13) 1.01 (0.89, 1.14) 1.00 (0.88, 1.14) 0.98 (0.85, 1.12) 0.67
Rectal
3
1.00 1.05 (0.87, 1.28) 0.97 (0.79, 1.19) 1.11 (0.90, 1.38) 0.91 (0.72, 1.15) 0.49
Rectal + recent adult intake
5
1.00 1.07 (0.89, 1.30) 1.00 (0.81, 1.23) 1.16 (0.94, 1.43) 0.97 (0.76, 1.23) 0.90
Milk
8
Median (times consumed/d) 0 0.50 0.79 1.00 3.00 —
Colon cancer (no. of cases) 220 648 427 602 903 —
Rectal cancer (no. of cases) 68 219 139 237 316 —
Colon
3
1.00 1.00 (0.86, 1.15) 0.89 (0.76, 1.06) 0.86 (0.73, 1.01) 0.84 (0.71, 0.99) 0.04
Colon + recent adult intake
5
1.00 1.00 (0.86, 1.17) 0.94 (0.79, 1.11) 0.91 (0.77, 1.07) 0.92 (0.78, 1.10) 0.42
Rectal
3
1.00 1.03 (0.78, 1.36) 0.91 (0.68, 1.23) 1.05 (0.79, 1.40) 0.94 (0.70, 1.26) 0.43
Rectal + recent adult intake
5
1.00 1.07 (0.79, 1.38) 0.93 (0.69, 1.26) 1.08 (0.81, 1.43) 0.99 (0.73, 1.34) 0.72
Red meat
9
Median (times consumed/d) 0.31 0.68 1.01 1.36 1.99 —
Colon cancer (no. of cases) 596 552 550 559 537 —
Rectal cancer (no. of cases) 205 178 201 194 201 —
Colon
3
1.00 1.01 (0.89, 1.14) 1.03 (0.91, 1.16) 1.12 (0.98, 1.28) 1.14 (0.97, 1.33) 0.05
Colon + recent adult intake
5
1.00 0.99 (0.88, 1.12) 1.00 (0.88, 1.14) 1.08 (0.95, 1.24) 1.09 (0.93, 1.28) 0.14
Rectal
3
1.00 0.92 (0.74, 1.13) 1.03 (0.83, 1.27) 1.06 (0.84, 1.33) 1.13 (0.87, 1.47) 0.19
Rectal + recent adult intake
5
1.00 0.90 (0.73, 1.11) 0.99 (0.80, 1.23) 1.01 (0.81, 1.27) 1.08 (0.83, 1.40) 0.35
Processed meat
10
Median (times consumed/d) 0.1 0.35 0.58 0.93 1.35 —
Colon cancer (no. of cases) 570 451 606 647 520 —
Rectal cancer (no. of cases) 194 134 227 228 196 —
Colon
3
1.00 0.97 (0.85, 1.10) 1.07 (0.94, 1.20) 1.11 (0.98, 1.25) 1.13 (0.98, 1.31) 0.03
Colon + recent adult intake
5
1.00 0.96 (0.85, 1.09) 1.05 (0.93, 1.19) 1.08 (0.95, 1.23) 1.11 (0.96, 1.28) 0.06
Rectal
3
1.00 0.81 (0.65, 1.01) 1.08 (0.88, 1.32) 1.04 (0.84, 1.32) 1.13 (0.89, 1.45) 0.10
Rectal + recent adult intake
5
1.00 0.80 (0.64, 1.00) 1.05 (0.86, 1.29) 1.01 (0.82, 1.25) 1.09 (0.85, 1.40) 0.18
Solid fat
11
Median (times consumed/d) 0.21 0.57 1.00 1.07 2.00 —
Colon cancer (no. of cases) 522 769 647 232 624 —
Rectal cancer (no. of cases) 177 270 228 93 211 —
Colon
3
1.00 1.01 (0.90, 1.13) 0.97 (0.85, 1.10) 0.88 (0.74, 1.04) 0.92 (0.80, 1.06) 0.26
Colon + recent adult intake
5
1.00 1.01 (0.90, 1.13) 0.96 (0.85, 1.09) 0.87 (0.74, 1.03) 0.92 (0.80, 1.05) 0.31
Rectal
3
1.00 1.03 (0.85, 1.25) 1.02 (0.83, 1.26) 1.01 (0.77, 1.32) 0.93 (0.77, 1.18) 0.58
Rectal + recent adult intake
5
1.00 1.01 (0.83, 1.23) 0.99 (0.80, 1.23) 0.98 (0.74, 1.28) 0.90 (0.71, 1.14) 0.60
Sweet baked goods
12
Median (times consumed/d) 0.10 0.30 0.63 1.00 1.79 —
Colon cancer (no. of cases) 595 569 513 571 546 —
Rectal cancer (no. of cases) 220 193 171 214 181 —
(Continued)
1612 RUDER ET AL
intake by sex showed a positive association among women in the
highest quintile of fiber intake during adolescence (HR: 1.29;
95% CI: 1.05, 1.59), but a nonsignificant inverse association
among men (HR: 0.95; 95% CI: 0.82, 1.11). However, for diet
10 y before baseline, this association was nonsignificantly
greater in women (HR: 1.15; 95% CI: 0.92, 1.43) but signifi-
cantly lower in men (HR: 0.78; 95% CI: 0.66, 0.93).
In an effort to determine how change in consumption patterns
over time affect colon and rectal cancer risk, we examined the
combinations of tertiles of intake at age 12–13 y and baseline in
1995 when the participants were 50–71 y of age. The percentage
of individuals belonging to the various tertile combinations
ranged from a low of 6.6% (for participants in the highest tertile
of consumption of calories, fat, or vegetables in adolescence but
in the lowest tertile of consumption for these dietary factors in
recent adulthood) to 22.8% of individuals who were high milk
consumers during both adolescence and recent adulthood).
Relative to individuals who were in the lowest tertile of con-
sumption at both time points, colon cancer risk was lower for
those in the highest tertile of consumption at both time points for
intakes of carbohydrate (HR: 0.86; 95% CI: 0.74, 1.00), calcium
(HR: 0.70; 95% CI: 0.61, 0.81), and vitamin A (HR: 0.83; 95%
CI: 0.72, 0.95) (Figure 1A). A significant inverse association
with vitamin A consumption was also observed when high
consumption occurred only in adolescence, and significant in-
verse associations between consumption of carbohydrate or
calcium and colon cancer were observed when high consump-
tion occurred in recent adult diet. Similar to the findings for
colon cancer, a lower risk of rectal cancer was observed among
individuals in the highest tertiles of consumption at both time
points for carbohydrate (HR: 0.67; 95% CI: 0.52, 0.87) and
calcium (HR: 0.76; 95% CI: 0.59, 0.99) (Figure 1B). Although
a significant inverse relation with rectal cancer was observed
among individuals who were high carbohydrate consumers (re-
cent adult diet), a significant inverse association between high
calcium intake and rectal cancer was observed only among in-
dividuals who were high consumers at both time points.
Analyses of the change in consumption of food groups (Figure
2) showed a lower risk of colon cancer among individuals in the
highest tertile as both adolescents and adults relative to those in
the lowest tertile at both time points for vegetables (HR: 0.84;
95% CI: 0.72, 0.97), fruit (HR: 0.83; 95% CI: 0.71, 0.97), and
milk (HR: 0.74; 95% 0.64, 0.85) (Figure 2A). Furthermore, the
reduction in colon cancer risk among high fruit consumers was
observed only with high fruit consumption in both time periods,
whereas the reduction in colon cancer with high milk con-
sumption was observed when consumption was high during
recent adult life, but not when consumption was high in ado-
lescence and low in recent adulthood. A greater risk of colon
cancer was noted among those with high consumption, at both
time points, of the following food groups relative to those with
low consumption at both time points: red meat (HR: 1.38; 95%
CI: 1.16, 1.64) and processed meat (HR: 1.25; 95% CI: 1.06,
1.47); the red meat association was evident if the individuals
were in the highest intake category at any point in time. Ex-
amination of rectal cancer showed a greater risk among in-
dividuals in the highest tertile of consumption at both time
points for red meat (HR: 1.39; 95% CI: 1.04, 1.85) (Figure 2B).
The association was not significant if high consumption oc-
curred only in adolescence or only in recent adulthood.
DISCUSSION
In this large prospective study, we found evidence that diet in
adolescence and mid-life, both of which are outside the time
period routinely assessed in nutritional epidemiology studies,
may modify the risk of colon and rectal cancer. Specifically, we
found that individuals with a high consumption of vitamin A or
vegetables during ages 12–13 y had a reduction in colon cancer
risk after age 50 y. Furthermore, a high intake of calcium, vitamin
A, or vitamin C during ages 40–61 y was inversely associated
with colon cancer after age 50 y. Similar protective associations
were observed among high consumers of fruit or milk during ages
40–61 y, and deleterious associations with colon cancer were
TABLE 3 (Continued )
Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5 P-trend
1
Colon
3
1.00 0.92 (0.81, 1.03) 0.95 (0.84, 1.08) 0.94 (0.82, 1.07) 1.02 (0.88, 1.18) 0.41
Colon + recent adult intake
5
1.00 0.92 (0.82, 1.03) 0.96 (0.85, 1.08) 0.94 (0.83, 1.07) 1.03 (0.89, 1.19) 0.35
Rectal
3
1.00 0.80 (0.66, 0.98) 0.81 (0.66, 1.00) 0.90 (0.73, 1.10) 0.82 (0.64, 1.06) 0.48
Rectal + recent adult intake
5
1.00 0.81 (0.66, 0.99) 0.82 (0.67, 1.01) 0.91 (0.74, 1.12) 0.84 (0.65, 1.07) 0.55
1
Linear test for trend derived by using the median value of each quintile.
2
White bread or rolls, dark bread or rolls (rye, whole grain, whole wheat, and pumpernickel), and pizza.
3
Adjusted for energy at ages 12–13 y, age at completion of risk-factor questionnaire, sex, BMI, race, education, physical activity, alcohol consumption,
smoking, use of aspirin and ibuprofen, use of hormone replacement therapy, and self-report of a first-degree relative with a history of colon cancer.
4
HR; 95% CI in parentheses (all such values); calculated by Cox proportional hazard regression models.
5
Adjusted for energy at ages 12–13 y, energy in recent adulthood, nutrient of interest in recent adulthood, age at completion of risk-factor questionnaire,
sex, BMI, race, education, physical activity, alcohol consumption, smoking, use of aspirin and ibuprofen, use of hormone replacement therapy, and self-report
of a first-degree relative with a history of colon cancer.
6
Broccoli, carrots, baked beans, lettuce salads, fresh tomato, tomato or vegetable soup, and other vegetables, including corn, peas, and green beans.
7
Fresh apples (not cooked), orange or grapefruit juice, oranges, grapefruit, tangerines, and canned fruit, such as peaches, pears, and applesauce.
8
Whole milk, including on cereals; categories of intake were assigned rather than quintiles because of clustering of intake frequency.
9
Ground beef, roast beef or steak, cold cuts, bacon or sausage, and hot dogs.
10
Bacon or sausage, cold cuts, and hot dogs.
11
Butter and margarine.
12
Cookies, cake, or donuts.
ADOLESCENT AND MID-LIFE DIET AND COLORECTAL CANCER 1613
TABLE 4
Multivariate risks for the association between intake of energy and nutrients 10 y before baseline and colorectal cancer in the NIH-AARP Diet and Health
Study (n= 295,845)
1
Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5 P-trend
2
Carbohydrate
Median (g/1000 kcal) 85 98 106 115 129 —
Colon cancer (no. of cases) 575 545 543 588 568 —
Rectal cancer (no. of cases) 193 193 206 202 191 —
Colon
3
1.00 0.80 (0.80, 1.01)
4
0.86 (0.77, 0.97) 0.90 (0.80, 1.01) 0.84 (0.74, 0.94) ,0.01
Colon + recent adult intake
5
1.00 0.92 (0.82, 1.04) 0.90 (0.80, 1.02) 0.95 (0.84, 1.07) 0.89 (0.78, 1.01) 0.13
Rectal
3
1.00 0.97 (0.80, 1.19) 1.01 (0.83, 1.23) 0.96 (0.79, 1.18) 0.90 (0.73, 1.10) 0.32
Rectal + recent adult intake
5
1.00 1.00 (0.81, 1.22) 1.05 (0.86, 1.29) 1.03 (0.84, 1.27) 1.00 (0.81, 1.24) 0.90
Total fat
Median (g/1000 kcal) 35 41 44 47 52 —
Colon cancer (no. of cases) 560 546 542 573 598 —
Rectal cancer (no. of cases) 179 205 215 196 192 —
Colon
3
1.00 0.99 (0.88, 1.12) 1.02 (0.90, 1.15) 1.10 (0.97, 1.24) 1.20 (1.06, 1.35) ,0.01
Colon + recent adult intake
5
1.00 0.99 (0.88, 1.12) 1.00 (0.88, 1.13) 1.06 (0.94, 1.21) 1.15 (1.01, 1.30) 0.02
Rectal
3
1.00 1.13 (0.92, 1.38) 1.21 (0.99, 1.48) 1.11 (0.90, 1.36) 1.09 (0.88, 1.34) 0.47
Rectal + recent adult intake
5
1.00 1.09 (0.88, 1.34) 1.15 (0.93, 1.41) 1.03 (0.83, 1.28) 1.00 (0.81, 1.25) 0.89
Protein
Median (g/1000 kcal) 32 37 41 44 50 —
Colon cancer (no. of cases) 585 577 544 573 540 —
Rectal cancer (no. of cases) 192 189 195 197 212 —
Colon
3
1.00 1.00 (0.89, 1.12) 0.95 (0.84, 1.07) 1.01 (0.90, 1.13) 0.94 (0.83, 1.06) 0.34
Colon + recent adult intake
5
1.00 1.02 (0.90, 1.14) 0.97 (0.86, 1.09) 1.03 (0.92, 1.16) 0.96 (0.85, 1.09) 0.61
Rectal
3
1.00 0.99 (0.81, 1.22) 1.03 (0.84, 1.26) 1.02 (0.83, 1.25) 1.08 (0.88, 1.32) 0.43
Rectal + recent adult intake
5
1.00 0.98 (0.80, 1.21) 1.02 (0.83, 1.25) 1.01 (0.82, 1.24) 1.06 (0.86, 1.30) 0.56
Fiber
Median (g/1000 kcal) 5 7 8 10 13 —
Colon cancer (no. of cases) 593 562 556 569 539 —
Rectal cancer (no. of cases) 177 198 216 202 192 —
Colon
3
1.00 0.95 (0.84, 1.06) 0.92 (0.82, 1.04) 0.94 (0.83, 1.05) 0.90 (0.80, 1.02) 0.12
Colon + recent adult intake
5
1.00 0.97 (0.86, 1.09) 0.97 (0.86, 1.09) 0.99 (0.88, 1.12) 0.97 (0.85, 1.10) 0.75
Rectal
3
1.00 1.11 (0.91, 1.36) 1.24 (1.01, 1.51) 1.17 (0.96, 1.44) 1.15 (0.93, 1.42) 0.25
Rectal + recent adult intake
5
1.00 1.13 (0.92, 1.39) 1.29 (1.05, 1.58) 1.24 (1.01, 1.54) 1.26 (1.00, 1.58) 0.06
Calcium
Median (mg/1000 kcal) 259 325 393 483 610 —
Colon cancer (no. of cases) 661 575 578 483 522 —
Rectal cancer (no. of cases) 217 232 177 178 181 —
Colon
3
1.00 0.84 (0.75, 0.95) 0.82 (0.73, 0.91) 0.68 (0.61, 0.77) 0.73 (0.65, 0.82) ,0.01
Colon + recent adult intake
5
1.00 0.88 (0.79, 0.99) 0.87 (0.78, 0.98) 0.75 (0.66, 0.85) 0.83 (0.73, 0.94) ,0.01
Rectal
3
1.00 1.05 (0.87, 1.26) 0.79 (0.64, 0.96) 0.79 (0.65, 0.97) 0.82 (0.67, 1.00) ,0.01
Rectal + recent adult intake
5
1.00 1.06 (0.88, 1.28) 0.81 (0.66, 0.99) 0.83 (0.67, 1.02) 0.85 (0.69, 1.06) 0.05
Vitamin A
Median (IU/1000 kcal) 1714 2492 3357 4683 8117 —
Colon cancer (no. of cases) 639 546 538 575 521 —
Rectal cancer (no. of cases) 203 224 189 172 197 —
Colon
3
1.00 0.83 (0.74, 0.93) 0.82 (0.73, 0.93) 0.88 (0.79, 0.99) 0.79 (0.71, 0.92) ,0.01
Colon + recent adult intake
5
1.00 0.84 (0.75, 0.95) 0.84 (0.75, 0.95) 0.91 (0.81, 1.03) 0.81 (0.71, 0.92) 0.03
Rectal
3
1.00 1.10 (0.91, 1.33) 0.96 (0.78, 1.17) 0.87 (0.71, 1.08) 1.02 (0.83, 1.24) 0.70
Rectal + recent adult intake
5
1.00 1.09 (0.90, 1.32) 0.96 (0.78, 1.17) 0.88 (0.71, 1.09) 1.05 (0.84, 1.30) 0.96
Vitamin C
Median (mg/1000 kcal) 31 55 81 112 169 —
Colon cancer (no. of cases) 654 545 547 550 523 —
Rectal cancer (no. of cases) 214 223 183 186 179 —
Colon
3
1.00 0.85 (0.76, 0.95) 0.84 (0.74, 0.94) 0.83 (0.74, 0.93) 0.78 (0.70, 0.88) ,0.01
Colon + recent adult intake
5
1.00 0.88 (0.78, 0.99) 0.88 (0.78, 1.00) 0.88 (0.77, 1.00) 0.83 (0.72, 0.95) 0.02
Rectal
3
1.00 1.08 (0.89, 1.30) 0.99 (0.75, 1.11) 0.91 (0.75, 1.11) 0.90 (0.74, 1.11) 0.13
Rectal + recent adult intake
5
1.00 1.09 (0.90, 1.33) 0.92 (0.75, 1.14) 0.95 (0.77, 1.18) 0.96 (0.77, 1.21) 0.48
1
A greater number of participants completed the food-frequency questionnaire about diet 10 y previously than about diet during ages 12–13 y. Thus, the
nvalues for Tables 4 and 5 are greater than those for Tables 2 and 3.
2
Linear test for trend derived by using the median value of each quintile.
3
Adjusted for energy at ages 12–13 y, age at completion of risk-factor questionnaire, sex, BMI, race, education, physical activity, alcohol consumption,
smoking, use of nonsteroidal antiinflammatory drugs, use of hormone replacement therapy, and self-report of a first-degree relative with a history of colon cancer.
4
HR; 95% CI in parentheses (all such values); calculated by Cox proportional hazard regression models.
5
Adjusted for energy at ages 12–13 y, energy in recent adulthood, nutrient of interest in recent adulthood, age at completion of risk-factor questionnaire,
sex, BMI, race, education, physical activity, alcohol consumption, smoking, use of nonsteroidal antiinflammatory drugs, use of hormone replacement therapy,
and self-report of a first-degree relative with a history of colon cancer.
1614 RUDER ET AL
TABLE 5
Multivariate risks for the association between food group intake 10 y before baseline and colorectal cancer in older adulthood in the NIH-AARP Diet and
Health Study (n= 295,845)
1
Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5 P-trend
2
Grains
3
Median (times consumed/d) 0.25 0.58 0.87 1.08 2.07 —
Colon cancer (no. of cases) 566 518 614 524 597 —
Rectal cancer (no. of cases) 172 195 219 181 218 —
Colon
4
1.00 0.98 (0.87, 1.10)
5
1.00 (0.88, 1.13) 1.10 (0.96, 1.25) 1.10 (0.96, 1.27) 0.09
Colon + recent adult intake
6
1.00 0.99 (0.88, 1.12) 1.02 (0.90, 1.15) 1.13 (0.99, 1.29) 1.14 (0.98, 1.31) 0.05
Rectal
4
1.00 1.19 (0.97, 1.47) 1.14 (0.92, 1.40) 1.22 (0.95, 1.55) 1.22 (0.95, 1.55) 0.26
Rectal + recent adult intake
6
1.00 1.21 (0.98, 1.49) 1.16 (0.94, 1.44) 1.24 (0.98, 1.56) 1.28 (1.00, 1.64) 0.12
Vegetables
7
Median (times consumed/d) 0.53 0.99 1.42 1.98 2.85 —
Colon cancer (no. of cases) 641 561 518 546 553 —
Rectal cancer (no. of cases) 194 197 201 190 203 —
Colon
4
1.00 0.90 (0.80, 1.01) 0.81 (0.72, 0.91) 0.84 (0.75, 0.95) 0.87 (0.77, 0.99) 0.06
Colon + recent adult intake
6
1.00 0.91 (0.81, 1.02) 0.82 (0.73, 0.93) 0.86 (0.76, 0.98) 0.88 (0.77, 1.01) 0.13
Rectal
4
1.00 1.06 (0.86, 1.29) 1.06 (0.87, 1.30) 1.01 (0.82, 1.25) 1.14 (0.92, 1.42) 0.33
Rectal + recent adult intake
6
1.00 1.04 (0.85, 1.28) 1.05 (0.86, 1.29) 0.99 (0.80, 1.24) 1.12 (0.88, 1.41) 0.47
Fruit
8
Median (times consumed/d) 0.16 0.56 0.99 1.35 2.10 —
Colon cancer (no. of cases) 637 550 558 533 541 —
Rectal cancer (no. of cases) 209 208 200 183 185 —
Colon
4
1.00 0.88 (0.79, 0.99) 0.86 (0.77, 0.97) 0.80 (0.70, 0.90) 0.82 (0.72, 0.92) ,0.01
Colon + recent adult intake
6
1.00 0.90 (0.80, 1.01) 0.89 (0.78, 1.01) 0.82 (0.72, 0.94) 0.84 (0.73, 0.97) 0.02
Rectal
4
1.00 1.03 (0.85, 1.26) 0.98 (0.81, 1.20) 0.88 (0.72, 1.08) 0.91 (0.73, 1.12) 0.17
Rectal + recent adult intake
6
1.00 1.07 (0.88, 1.31) 1.05 (0.85, 1.29) 0.97 (0.77, 1.21) 1.05 (0.82, 1.34) 0.96
Milk
9
Median (times consumed/d) 0.03 0.28 0.79 1.0 2.0 —
Colon cancer (no. of cases) 628 660 503 555 473 —
Rectal cancer (no. of cases) 218 227 186 182 172 —
Colon
4
1.00 0.85 (0.76, 0.95) 0.81 (0.72, 0.92) 0.73 (0.65, 0.82) 0.70 (0.61, 0.79) ,0.01
Colon + recent adult intake
6
1.00 0.88 (0.79, 0.99) 0.87 (0.76, 0.98) 0.79 (0.69, 0.90) 0.78 (0.67, 0.90) ,0.01
Rectal
4
1.00 0.83 (0.69, 1.00) 0.87 (0.71, 1.06) 0.69 (0.56, 0.85) 0.74 (0.59, 0.92) ,0.01
Rectal + recent adult intake
6
1.00 0.81 (0.67, 0.99) 0.85 (0.69, 1.06) 0.68 (0.54, 0.85) 0.75 (0.58, 0.96) 0.05
Red meat
10
Median (times consumed/d) 0.18 0.43 0.66 0.96 1.49 —
Colon cancer (no. of cases) 516 556 571 552 624 —
Rectal cancer (no. of cases) 174 175 197 209 230 —
Colon
4
1.00 1.13 (1.00, 1.28) 1.17 (1.03, 1.33) 1.23 (1.08, 1.41) 1.46 (1.26, 1.69) ,0.01
Colon + recent adult intake
6
1.00 1.09 (0.96, 1.24) 1.10 (0.96, 1.25) 1.14 (0.99, 1.31) 1.31 (1.12, 1.53) ,0.01
Rectal
4
1.00 1.00 (0.81, 1.24) 1.08 (0.88, 1.34) 1.21 (0.97, 1.51) 1.24 (0.97, 1.59) 0.03
Rectal + recent adult intake
6
1.00 0.95 (0.76, 1.18) 0.99 (0.79, 1.24) 1.07 (0.85, 1.36) 1.06 (0.81, 1.38) 0.42
Processed meat
11
Median (times consumed/d) 0.05 0.15 0.30 0.53 1.02 —
Colon cancer (no. of cases) 411 576 571 617 644 —
Rectal cancer (no. of cases) 120 201 205 214 245 —
Colon
4
1.00 1.03 (0.90, 1.17) 1.11 (0.98, 1.27) 1.24 (1.09, 1.42) 1.30 (1.13, 1.51) ,0.01
Colon + recent adult intake
6
1.00 1.02 (0.89, 1.16) 1.09 (0.95, 1.25) 1.20 (1.04, 1.39) 1.24 (1.06, 1.45) ,0.01
Rectal
4
1.00 1.19 (0.95, 1.50) 1.26 (1.00, 1.59) 1.31 (1.03, 1.66) 1.40 (1.09, 1.81) 0.02
Rectal + recent adult intake
6
1.00 1.18 (0.93, 1.49) 1.21 (0.95, 1.54) 1.24 (0.96, 1.59) 1.30 (0.99, 1.70) 0.16
Solid fat
12
Median (times consumed/d) 0.08 0.50 0.79 1.00 2.00 —
Colon cancer (no. of cases) 563 631 521 545 559 —
Rectal cancer (no. of cases) 186 241 176 203 179 —
Colon
4
1.00 0.99 (0.88, 1.11) 1.01 (0.89, 1.14) 0.96 (0.85, 1.09) 1.05 (0.92, 1.19) 0.42
Colon + recent adult intake
6
1.00 0.98 (0.87, 1.10) 0.99 (0.87, 1.12) 0.94 (0.83, 1.07) 1.01 (0.89, 1.15) 0.80
Rectal
4
1.00 1.12 (0.92, 1.36) 0.99 (0.80, 1.23) 1.07 (0.87, 1.31) 0.97 (0.78, 1.21) 0.52
Rectal + recent adult intake
6
1.00 1.07 (0.88, 1.30) 0.93 (0.75, 1.15) 0.99 (0.80, 1.21) 0.87 (0.69, 1.09) 0.11
Sweet baked goods
13
Median (times consumed/d) 0.05 0.20 0.35 0.73 1.35 —
Colon cancer (no. of cases) 636 445 596 578 564 —
Rectal cancer (no. of cases) 228 167 190 203 197 —
(Continued)
ADOLESCENT AND MID-LIFE DIET AND COLORECTAL CANCER 1615
observed among those with a high intake of fat, red meat, and
processed meat during ages 40–61 y and for processed meat and
rectal cancer. In addition, significant P-trend values indicating
a dose-response relation were observed for all but one of the
aforementioned dietary variables.
A novel aspect of our study was the evaluation of how dietary
change over time affects colorectal cancer risk. We found
multiple instances in which an effect was observed when con-
sumption was high in both adolescence and recent adult life, but
not when consumption was low in adolescents who became high
consumers as adults or vice versa. This suggests that the pattern of
exposure over the life course may play an important role in
colorectal cancer risk.
Validation studies of diet recalled in the distant past are
limited. Reproducibility among responses to an FFQ about diet
during high school (15–35 y in the past) among Nurses’ Health
TABLE 5 (Continued )
Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5 P-trend
2
Colon
4
1.00 0.89 (0.79, 1.01) 1.04 (0.92, 1.17) 0.99 (0.88, 1.11) 1.02 (0.90, 1.15) 0.47
Colon + recent adult intake
6
1.00 0.90 (0.79, 1.02) 1.04 (0.93, 1.17) 0.99 (0.88, 1.12) 1.01 (0.89, 1.15) 0.54
Rectal
4
1.00 0.93 (0.76, 1.13) 0.89 (0.73, 1.07) 0.92 (0.75, 1.10) 0.92 (0.75, 1.10) 0.61
Rectal + recent adult intake
6
1.00 0.94 (0.77, 1.16) 0.91 (0.74, 1.11) 0.94 (0.77, 1.15) 0.93 (0.75, 1.15) 0.66
1
A greater number of participants completed the food-frequency questionnaire about diet 10 y previously than about diet during ages 12–13 y. Thus, the
nvalues for Tables 4 and 5 are greater than those for Tables 2 and 3.
2
Linear test for trend derived by using the median value of each quintile.
3
White bread or rolls, dark bread or rolls (rye, whole grain, whole wheat, and pumpernickel), and pizza.
4
Adjusted for energy at ages 12–13 y, age at completion of risk-factor questionnaire, sex, BMI, race, education, physical activity, alcohol consumption,
smoking, use of aspirin and ibuprofen, use of hormone replacement therapy, and self-report of a first-degree relative with a history of colon cancer.
5
HR; 95% CI in parentheses (all such values); calculated by Cox proportional hazard regression models.
6
Adjusted for energy at ages 12–13 y, energy in recent adulthood, nutrient of interest in recent adulthood, age at completion of risk-factor questionnaire,
sex, BMI, race, education, physical activity, alcohol consumption, smoking, use of aspirin and ibuprofen, use of hormone replacement therapy, and self-report
of a first-degree relative with a history of colon cancer.
7
Broccoli, carrots, baked beans, lettuce salads, fresh tomato, tomato or vegetable soup, and other vegetables, including corn, peas, and green beans.
8
Fresh apples (not cooked), orange or grapefruit juice, oranges, grapefruit, tangerines, and canned fruit such as peaches, pears, and applesauce.
9
Whole milk, including on cereals; categories of intake were assigned rather than quintiles because of clustering of intake frequency.
10
Ground beef, roast beef or steak, cold cuts, bacon or sausage, and hot dogs.
11
Bacon or sausage, cold cuts, and hot dogs.
12
Butter and margarine.
13
Cookies, cake, or donuts.
FIGURE 1. HRs and 95% CIs for colon cancer (A) and rectal cancer (B) by change in tertiles of nutrient intakes from adolescence to recent adulthood
relative to individuals in the lowest tertile of intake at both time points.
1616 RUDER ET AL
Study II participants indicated moderate to strong reproducibility
(20). Furthermore, correlation between FFQ responses by the
nurses and their mothers regarding their child’s diet were also
moderate. However, validation of parental 7-d food records re-
garding the diet of their 13–18-y-old children from the Fels
Longitudinal Study were generally not well correlated with the
offspring’s response to an FFQ administered roughly 48 y later,
although there was variation ranging from 20.53 to 0.99 (21).
Although the ideal study design would ascertain diet in youth
and prospectively follow participants for decades until cancer
incidence, the methods used in the current investigation are
among the best available to address life course exposures in
relation to cancer in the absence of this archetype, a topic that is
designated as a “research priority” by the American Institute for
Cancer Research (22).
The 37-item FFQs used in our study considered select nutrients
and food groups, and the food-group assessment did not disag-
gregate complex mixtures of food. A comparison of nutrient
values derived from our FFQ about diet during adolescence with
those estimated for 12–13-y-olds in the HFCS indicated higher
values for the HFCS. This finding is not surprising given that our
FFQ consisted of only 37 items and the HFCS had an open-ended
recall. Despite the lower estimates of intake, we expect that
the ranking is accurate. In addition, it is possible that mis-
classification of self-reported lifestyle characteristics occurred; if
misclassification was nondifferential, the results would most likely
be biased toward the null (23). The strengths of our study included
the large study population, which accrued 2794 colon and 979
rectal cancers, and the use of period-relevant nutrition surveys and
databases to estimate serving size and nutrient information.
Evidence from the Netherlands Cohort Study suggests that
adolescence and early adulthood are critical periods for epige-
netic modification associated with future colorectal cancer risk
(9). Recent work from the same cohort documented lower colon
cancer risk among men who experienced severe caloric re-
striction during adolescence (8). Few studies have examined
intakes of specific nutrients or food groups during adolescence
and the risk of colorectal cancer. Prospective dietary data col-
lected during adolescence showed a positive association between
dairy product intake and colorectal cancer risk in the British-
based Boyd-Orr cohort (11). This is somewhat surprising given
that milk and calcium intake in adulthood are generally asso-
ciated with a lower risk of colorectal cancer (2), although the
small number of colorectal cancer cases (n= 76) is important to
note. Contrary to the Boyd Orr findings, a recent study of par-
ticipation in New Zealand government-sponsored school milk
programs indicated a reduced colorectal cancer risk with pro-
gram participation, including evidence of a dose-response effect
with increased milk consumption (10). In our study, after control
for recent adult intake, the associations for calcium and milk
intakes during adolescent in relation to colon cancer were at-
tenuated. Adult dietary consumption was not investigated in the
New Zealand Study.
We found significant inverse relations between vegetable and
vitamin A intakes during adolescence and colon cancer. Post hoc
analyses indicated that the top 3 adolescent contributors to vi-
tamin A intake (carrots, whole milk, and tomato or other veg-
etables soups) provided ;54% of this nutrient; because 2 of the
3 leading contributors to vitamin A are vegetables, it is not
surprising that both vitamin A and vegetables were inversely
associated with colon cancer. Recent vegetable intake in adults
was previously shown to be associated with a reduction in co-
lorectal cancer among men in the NIH-AARP Diet and Health
Study (24).
Although certain cohort studies have .20 y of follow-up
data, data are lacking on the association of dietary exposures
FIGURE 2. HRs and 95% CIs for colon cancer (A) and rectal cancer (B) by change in tertiles of food group intakes from adolescence to recent adulthood
relative to individuals in the lowest tertile of intake at both time points.
ADOLESCENT AND MID-LIFE DIET AND COLORECTAL CANCER 1617
corresponding to mid-life with the outcome of colorectal cancer
after control for more recent dietary exposure. Given the natural
history of the adenoma-carcinoma sequence (25), it is reasonable
to hypothesize that diet in mid-life could be an important expo-
sure period for colorectal cancer—a malignancy that typically
occurs after the sixth decade of life. Results from our study in-
dicate that certain nutrients and food groups consumed during
the ages 40–61 y were associated with risk of colorectal cancer
10–20 y in the future, independent of future dietary characteristics.
This suggests that dietary intake earlier in the life course than
previous explored (24, 26–29) may play a role in colorectal cancer.
Our finding that fiber consumption in the highest quintile
during adolescence was positively associated with rectal cancer
was unexpected, as were the results from sex-stratified analyses
of fiber and colon cancer suggesting an greater risk of colon
cancer among women with high fiber consumption during ad-
olescence. Fiber was the only nutrient for which period-relevant
nutrient data were not available; fiber values from NHANES
1999–2000 were imputed for all 3 time points and may have been
a source of error. Furthermore, median adolescent fiber intake
from the FFQ was 8.7 g/d, which is well below the amount (.30
g/d) reported in other studies reporting an inverse relation be-
tween fiber and colorectal cancer (30).
Our analyses of combinations of consumption levels during
adolescence and recent adulthood attempted to address the rel-
ative importance of life stages on cancer risk. Our results indicate
that, for certain dietary exposures, the protective or deleterious
effect was present only when individuals were high consumers in
both adolescence and recent adulthood. We found evidence that
the pattern of exposure over the life course was particularly
relevant for a protective effect of fruit against colon cancer and of
calcium against rectal cancer and for the adverse relations be-
tween processed meat and colon cancer and between red meat
and rectal cancer.
In summary, our results suggest that certain dietary exposures
during ages 12–13 y are associated with colorectal cancer dec-
ades later, and certain dietary exposures during ages 40–61 y are
associated with colorectal cancer 10–20 y in the future. Expo-
sures during both time points are associated with colon or rectal
cancer independent of dietary exposures occurring closer in time
to the cancer diagnosis. Our results indicate that exposure over
the life course likely plays a significant role in determining
colorectal cancer risk. This is among the first investigations to
determine a role of diet during adolescence and mid-life on
colorectal carcinogenesis. Future studies are required to confirm
these findings.
We are indebted to the participants in the NIH-AARP Diet and Health
Study for their outstanding cooperation. We also thank Sigurd Hermansen
and Kerry Grace Morrissey from Westat for study outcomes ascertainment
and management and Leslie Carroll at Information Management Services
for data support and analysis. We acknowledge the loss and memory of Arthur
Schatzkin, who died 20 January 2011. He conceived and launched the NIH-
AARP Diet and Health Study and had great personal warmth and humor, tre-
mendous intellectual curiosity and honesty, a genuine interest in all, and a pas-
sion for improving public health through exemplary science. He will be dearly
missed. Cancer incidence data from the Atlanta metropolitan area were col-
lected by the Georgia Center for Cancer Statistics, Department of Epidemi-
ology, Rollins School of Public Health, and Emory University. Cancer
incidence data from California were collected by the California Department
of Health Services and Cancer Surveillance Section. Cancer incidence data
from the Detroit metropolitan area were collected by the Michigan Cancer
Surveillance Program, Community Health Administration, and the State of
Michigan. The Florida cancer incidence data used in this report were collected
by the Florida Cancer Data System (FCDC) under contract with the Florida
Department of Health (FDOH). Cancer incidence data from Louisiana were
collected by the Louisiana Tumor Registry and Louisiana State University
Medical Center in New Orleans. Cancer incidence data from New Jersey were
collected by the New Jersey State Cancer Registry, Cancer Epidemiology
Services, New Jersey State Department of Health and Senior Services. Cancer
incidence data from North Carolina were collected by the North Carolina Cen-
tral Cancer Registry. Cancer incidence data from Pennsylvania were supplied
by the Division of Health Statistics and Research, Pennsylvania Department
of Health, Harrisburg, PA. Cancer incidence data from Arizona were collected
by the Arizona Cancer Registry, Division of Public Health Services, Arizona
Department of Health Services. Cancer incidence data from Texas were col-
lected by the Texas Cancer Registry, Cancer Epidemiology and Surveillance
Branch, Texas Department of State Health Services.
The authors’ responsibilities were as follows—EHR, ACMT, YP, and AJC:
contributed to the analysis and drafting of the manuscript; FET, NP, and AFS:
contributed to the development of the FFQ, the data analysis, and the drafting
of the manuscript; BIG: contributed to the statistical analysis and drafting of
the manuscript; and ARH: contributed to the study design and concept. None
of the authors declared any conflicts of interest. The views expressed herein
are solely those of the authors and do not necessarily reflect those of the FCDC
or FDOH. The Pennsylvania Department of Health specifically disclaims re-
sponsibility for any analyses, interpretations, or conclusions.
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