The Journal of Nutrition
The Examination of Two Short Dietary Assessment Methods, within the Context of Multiple Behavioral Change
Interventions in Adult Populations
Correspondence of the NCI Fruit and Vegetable
Screener to Repeat 24-H Recalls and Serum
Carotenoids in Behavioral Intervention Trials1,2
Geoffrey W. Greene,3* Ken Resnicow,4Frances E. Thompson,5Karen E. Peterson,6Thomas G. Hurley,7
James R. Hebert,7Deborah J. Toobert,8Geoffrey C. Williams,9Diane L. Elliot,10Tamara Goldman Sher,11
Andrea Domas,12Douglas Midthune,13Maria Stacewicz-Sapuntzakis,14Amy L. Yaroch,15and Linda Nebeling15
3Department of Nutrition and Food Sciences, University of Rhode Island, Kingston, RI 02881;4Health Behavior and Health Education,
School of Public Health, University of Michigan, Ann Arbor, MI 48109-2029;5Applied Research Program, Division of Cancer Control and
Population Sciences, National Cancer Institute, Bethesda, MD 20892-7344;6Departments of Nutrition and Society, Human Development
and Health, Harvard School of Public Health, Boston, MA 02115;7Cancer Prevention and Control Program and Department of
Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC 29208;8Oregon Research
Institute, Eugene, OR 97403;9Departments of Medicine, Clinical and Social Sciences in Psychology, Psychiatry University of Rochester,
Rochester, NY 14642;10Division of Health Promotion and Sports Medicine, Oregon Health and Science University, Portland, OR 97239;
11Illinois Institute of Technology, Institute of Psychology, Chicago, IL 60616;12Rush University Medical Center, Department of Food and
Nutrition Services, Chicago, IL 60612;13Biometry Program, Division of Cancer Prevention, National Cancer Institute, Bethesda, MD
20892-7344;14Department of Kinesiology and Nutrition, University of Illinois at Chicago, Chicago IL 60612; and15Behavioral Research
Program, Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD 20892-7344
Five sites participating in the NCI Behavior Change Consortium administered the NCI Fruit and Vegetable Screener (FVS)
and multiple, nonconsecutive 24-h dietary recall interviews (24HR) to 590 participants. Three sites also obtained serum
carotenoids (n ¼ 295). Participants were primarily female, ethnically diverse, and varied by age and education. Correlations
between 24HR and FVS by site ranged from 0.31 (P ¼ 0.07) to 0.47 (P , 0.01) in men and from 0.43 to 0.63 (P , 0.01) in
women. Compared with 24HR, FVS significantly (P , 0.05) overestimated intake at 2 of 4 sites for men and all 4 sites for
women. Differences in estimated total servings of fruits and vegetables/d ranged from 0.16 to 3.06 servings. On average,
the FVS overestimated intake by 1.76 servings in men and 2.11 servings in women. Alternative FVS scoring procedures
and a 1-item screener lowered correlations with 24HR as well as serum carotenoids but alternate scoring procedures
generally improved estimations of servings.J. Nutr. 138: 200S–204S, 2008.
Higher intake of a variety of fruits and vegetables (FV)16is
associated with a reduced risk of many chronic diseases (1). The
2005 Dietary Guidelines for Americans (2) and Healthy People
2010 (3) promote daily intakes of FV (3.5–6.5 cups; 7–13 serv-
ings) that exceed previously recommended levels (4). However,
despite intervention programs (5), intake in the U.S. adult popu-
lation generally remains well below federal recommendations (6).
Accurate measurement of dietary intake is a major challenge
for health promotion research focusing on FV consumption. No
‘‘gold standard’’ provides a reference measurement of true in-
take, but repeat 24-h dietary recall interviews (24HR) have been
the cornerstone of the U.S. national nutrition surveillance system
(7). Although there are no recovery biomarkers to quantify FV
1Published ina supplement to The Journal of Nutrition. This effort was organized
by the National Cancer Institute (NCI) and the Behavior Change Consortium
(BCC) Nutrition Working Group (NWG) to present the outcome data from a
multidisciplinary collaboration from 7 BCC sites and 2 federal agencies:
University of Rhode Island, Harvard School of Public Health, Oregon Health &
Science University, Oregon Research Institute, Illinois Institute of Technology,
Emory University, University of Rochester, the NCI, and the Office of Dietary
Supplements. The BCC NWG was supported by National Institutes of Health
funding initiative RFA OD-93-002 with additional NCI supplemental funding
R01AG16588, R01HD37368, R01AR45901,
R01HL64959, and R01MH59594. The opinions or assertions contained herein
are the private ones of the authors and are not to be considered as official or
reflecting the views of the National Institutes of Health. Guest Editors: Shirley
A. A. Beresford, University of Washington, Seattle, WA and Lisa M. Klesges, St.
Jude Children’s Research Hospital, Memphis, TN, and Helaine R. H. Rockett,
Harvard Medical School and Brigham and Women’s Hospital, Boston, MA. Guest
Editor disclosure: S. A. A. Beresford, L. M. Klesges, and H. R. H. Rockett will
receive compensation from NCI, DCCPS, BRP for editorial services provided for
this supplement publication; L. M. Klesges was a member of the BCC.
2Author disclosures: G. W. Greene, K. Resnicow, C. F. E. Thompson, K. E.
Peterson, T. G. Hurley, J. R. Hebert, D. J. Toobert, G. C. Williams, D. L. Elliot, T.
Goldman Sher, A. Domas, D. Midthune, M. Stacewicz-Sapuntzakis, A. L. Yaroch,
and L. Nebeling, no conflicts of interest.
16Abbreviations used: 24HR, 24-h recalls; FV, fruit and vegetables; FVS, NCI
Fruit and Vegetable Screener; SC, serum carotenoids; Emory, Emory University;
HSPH, Harvard School of Public Health; IIT/Rush, Illinois Institute of Technology,
Rush University; NCI, National Cancer Institute; OHSU, Oregon Health & Science
University; ORI, Oregon Research Institute; ROC, University of Rochester; URI,
University of Rhode Island; USDA, United States Department of Agriculture.
* To whom correspondence should be addressed. E-mail: firstname.lastname@example.org.
0022-3166/08 $8.00 ª 2008 American Society for Nutrition.
by guest on December 30, 2011
intake, moderate correlations of serum carotenoids (SC) with
dietary FV have been observed in controlled feeding trials (8).
However, SC levels reflect metabolic processes also (9) as well as
environmental factors (10), thus effectively reducing correla-
tions with dietary intake (7).
In response to the need for program evaluation instruments,
several short food frequency instruments assessing only FV in-
take, without portion size, have been developed, including a
single-item instrument. In general, though, these instruments
underestimate intake (11). In 1998 the National Cancer Institute
(NCI) developed a revised Fruit and Vegetable Screener (FVS)
that added explicit portion size questions (12) (http://riskfactor.
cancer.gov/diet/screeners/fruitveg/allday.pdf). In a nationwide
sample of adults, the FVS produced relatively accurate estimates
of FV intake consistent with intake as measured using multiple
24HR (12). Scoring the FVS without portion size questions (fre-
quency alone) led to an underestimation of intake (12,13); al-
though using estimated portion sizes decreased the magnitude of
the underestimation, estimated intake remained low compared
with 24HR (13,14).
The primary validation studies of the FVS have been con-
ducted in predominantly white, well-educated population sam-
ples in dietary assessment research (12–13). The current study
was designed to evaluate the FVS among study participants in 5
ethnically and age diverse adult target populations (15). The
primary purpose of this article is to assess the correlation
between FV intake estimates derived from the FVS as compared
with multiple 24HR as well as to assess correlations of the FVS
with SC levels among participants enrolled in health promotion
trials. Secondary purposes include 1) assessment of the differ-
ence in intake estimated by the FVS and intake estimated from
24HR including ability to rank participants according to level of
intake (e.g., 24HR intake , 5 servings/d), and 2) exploration of
the correlation of alternative scoring procedures for the FVS as
well as the 1-item measure with multiple 24HR as well as SC.
Materials and Methods
Subjects. Evaluation of the FVS in the Behavioral Change Consortium
(BCC) was restricted to subjects at 5 sites with 24HR and complete FVS
data (n ¼ 590).17Sites were in the Northeast, Midwest, and South:
University of Rhode Island (URI), Harvard School of Public Health
(HSPH), Illinois Institute of Technology/Rush University (IIT/Rush),
Emory University (Emory), and University of Rochester (ROC). SC were
collected only at URI, IIT/Rush, and Emory (n ¼ 295).18For secondary
analyses of different FVS scoring procedures and the 1-item screener, the
sample size was 519.19
Dietary assessment. Sites administering 24HR utilized similar multi-
passmethodology; servingsof FV werecalculatedbasedon gramweights
consumed and USDA Pyramid equivalences from USDA’s Food and
Nutrient Database for Dietary Studies [see Yaroch et al. for a more
detailed description (15)].
The NCI FVS is a 19-item instrument querying the frequency of usual
consumption of 10 categories of FV over the past month (12) (http://
riskfactor.cancer.gov/diet/screeners/fruitveg/allday.pdf). Portion sizes are
queried for 9 items: 100% juice, fruit, lettuce salad, French fries/fried
potatoes, other white potatoes, cooked dried beans, other vegetables,
tomato sauce, and vegetable soups. A single item asking the frequency of
consuming ‘‘mixtures that included vegetables’’ was not included in ana-
lyses. The screener estimates daily servings of FV using the 1992 USDA
Food Guide Pyramid defined servings (16). For this study, all food
categories, including French fries, were included. Although designed to
be scoredusing respondent-assessedportion size (frequency3 respondent-
assessed portion size), the FVS also was scored using frequency alone
(FVS-frequency) and using external estimates of portion size with
3 estimated portion size based on CSFII age- and gender-specific median
portion sizes)] (13,14).
URI, HSPH, and ROC used a single-item global self-assessment of
servings of FV usually eaten (17), and Emory used a 2-item assessment (1
for fruits, the other for vegetables; items were summed for analysis) (18).
Response categories ranged from 0 to 6 or more daily (coded as 6). Emory
asked this range for both items; for consistency, daily servings were
truncated at 6.
Biochemical assessment. Blood was collected from an antecubital
vein after an overnight fast, centrifuged at 1500 3 g, and refrigerated for
15 to 20 min. After the centrifugation, 0.5 to 1.0 mL serum was trans-
ferred into a cryotube. Samples were stored at 270?C to 280?C until
shipment (express mail, packed in dry ice) to a laboratory at the Uni-
versity of Illinois at Chicago. Levels of 5 major carotenoids (a-carotene,
b-carotene, b-cryptoxanthin, lutein/zeaxanthin, and lycopene) were
determined by an established method (19). The reliability of the assay
was previously confirmed with blind control samples with coefficients of
variability 5 to 6% (20). The laboratory is a reference laboratory for the
National Institute of Standards and Technology’s (Gaithersburg, MD)
quality assurance program for carotenoids (21). Consistent with prior
biomarker studies, results are reported without lycopene (10).
Statistical analyses. Before analysis, 24HR and FVS were square-root
transformed, and SC was log transformed. Statistical tests are based on
transformed values and are back-transformed for presentation. One
extreme (.3 times the interquartile range above quartile 3) value of FV
intake was identified for FVS and excluded. All primary analyses are
presented separately by site and gender (as these factors were significant
modifiers of agreement based on 22 log likelihood ratios). Comparisons
of mean FV intake were tested using analysis of variance (ANOVA; Proc
GLM in SAS 9.1). A measurement error model (ME) was applied in this
study, as described in Freedman et al. (22), to deattenuate estimated
correlations between the multiple 24HR and other instruments and SC.
Correlations between the various dietary measures and SC were
estimated for each site and gender using Proc Corr (SAS 9.1). Partially
adjusted correlations controlling for site and age, and fully adjusted
correlations, in addition controlling for smoking, multivitamin use, and
BMI, were estimated (23). A limitation of the study was the inability to
adjust correlations for serum cholesterol (10) because serum cholesterol
was not assessed at all sites.
Participants were primarily female (72%), ethnically diverse
(51% white), and varied by age (40% $ 60 y) and education
(49% # high school/GED) (Table 1).
Correlations between FVS and 24HR were positive and
statistically significant in 2 of 3 sites for men and in all 4 sites for
women, ranging from 0.31 to 0.47 among men and 0.43 to 0.63
among women (Table 2). Correlations between servings of FV
calculated from the FVS and the sum of major SC without
lycopene were not statistically significant for men (0.02 to 0.24)
but were among women at 1 site (0.43) and not at the other
(0.24). With adjustment for site and age, correlations of FVS and
SC without lycopene were not statistically significant for men
(0.12) but were significant for women (0.30, P , 0.001) (data
not shown). Additional adjustments for smoking, multivitamin
use, and BMI did not materially affect what was observed with
just age and site adjustment. Agreement in 24HR and FVS
17Women in the IIT/Rush sample were excluded from the analytical sample
because of small numbers (n ¼ 5).
18Although ROC also collected SC, ROC data were excluded from analyses
because their use of a different laboratory resulted in noncomparable SC
19IIT/Rush did not administer the 1-item screener.
Evaluation of the NCI Fruit and Vegetable Screener201S
by guest on December 30, 2011
estimates of FV varied by site and gender (Table 2). Compared
with 24HR, FVS significantly (P , 0.05) overestimated intake at
2 of 4 sites for men and all 4 sites for women. Differences ranged
from 0.16 to 3.06 servings. On average, the FVS overestimated
intake by 1.76 servings in men and 2.11 servings in women. This
overestimation was reflected in a relatively low positive predic-
tive value of FVS to detect 24HR intake $ 5 servings/d (0.11 to
0.63 men; 0.20 to 0.62 women) but a high negative predictive
value to detect 24HR intake , 5 servings/d (0.64 to 0.85 men;
0.83 to 0.95 women).
Table 3 presents correlations in the subsample with the 1 item
(n ¼ 519) between 24HR and alternative screener scoring meth-
ods and the 1-item measure. Correlations between 24HR and all
3 instruments (FVS-frequency, FVS-estimate, 1-item) were not
(0.21 to 0.55). Site- and age-adjusted correlations between sum
Demographic characteristics of subjects (n ¼ 590)
URI, n ¼ 176 HSPH, n ¼ 105
(physical activity; diet)
IIT/Rush, n ¼ 57Emory, n ¼ 276ROC, n ¼ 97
(physical activity; diet)
Couples: cardiac risk
reduction (diet; other)
(physical activity; diet)
Smoking, diet, and
health (diet; other)
60 or older
# HS/TS grad or GED2
College grad or more
Underweight (BMI , 18.5)
Normal (18.5 , BMI , 24.9)
Overweight (25 , BMI , 29.9)
Obese (BMI $ 30)
0 57 (100%)
58 (60%)105 (100%)
11 (11%)176 (100%)
0 1 (1%)
0 1 (1%)
1Statistical difference by category between sites (x2).
2Includes ,8th grade, some HS, technical or vocational school, and HS or tech grad or GED.
3Other includes Asian, Pacific Islander, American Indian, Alaskan, Portuguese, and other groups.
*** P , 0.001.
by guest on December 30, 2011
and not statistically significant for men (0.08 to 0.20) but were
higher and statistically significant for women (0.15 to 0.23, P ,
servings in men and 0.20 servings in women. The overestimation
with FVS-estimate was 0.97 servings in men and 0.83 servings in
women. The 1-item underestimated intake by 1.14 servings in
men and 0.75 servings in women.
The FVS has been evaluated previously, in a general population
not enrolled in a dietary intervention trial (12). The NIH-funded
BCC (15) allowed evaluation of the instrument in intervention
settings. Published findings for the Emory site indicated low to
moderate correlations in the range of validity coefficients for
other self-report dietary measures (24). Our paper reports
analyses for all 5 participating sites, and is unique in examining
the correlation between the FVS and 24HR as well as SC in
diverse study populations enrolled in intervention trials with
dietary components. In addition, this study examined the effects
instrument. Results may be useful for researchers selecting
populations. Although the FVS generally overestimated intake
compared with 24HR, alternative scoring methods and the 1-
item instrument reduced this difference. These findings suggest a
bias in FVS estimates of intake among participants in behavioral
intervention studies even at baseline before intervention assign-
ment, which may limit their utility as an absolute measure of
intake. Calibration of the FVS in the target population with a
criterion measure such as multiple 24HR is recommended.
The overestimation of intake found with FVS relative to
24HR was associated with a high negative predictive value
indicating that the instrument would be effective in identifying
subjects with a low intake. However, in studies where subjects
with intake above a specific predetermined threshold are ex-
cluded, the relatively low positive predictive values (indicative of
overreporting of FV intake) suggest that many potentially eli-
gible subjects would be excluded. This could increase the pool of
subjects needing to be screened.
Estimated mean fruit and vegetable intake from 24HR, NCI respondent portion size scored fruit and vegetable screener
(FVS-RPS) the Pearson correlation coefficient between 24HR, the FVS-RPS and serum carotenoids without lycopene (SC),
by site and gender
Mean (95% CI1) Difference2(P-value)Pearson correlation coefficient (P-value)
FVS-24HR24HR and FVS4
24HR and FVS5
24HR and FVS4
50 5.26 (4.58–6.00)
0.31 (P ¼ 0.07)
0.63 (P # 0.0001)
0.02 (P ¼ 0.89)
0.43 (P # 0.0001)
0.23 (P ¼ 0.29)
0.56 (P # 0.0001) 126
105 3.36 (2.89–3.87) 4.94 (4.36–5.56)1.58 (,0.0001) 0.44 (P # 0.001)
575.09 (4.38–5.85) 5.24 (4.35–6.22)0.16 (0.73) 0.47 (P # 0.001)0.24 (P ¼ 0.13)0.53 (P ¼ 0.001)
17 4.04 (3.30–4.85)
1320.43 (P ¼ 0.01) 0.17 (P ¼ 0.07)0.53 (P # 0.0001)
0.46 (P ¼ 0.01)
0.47 (P # 0.001)
1CI ¼ confidence interval.
2The difference is calculated as FVS-24HR using the back-transformed values; the P-value test H0: Difference ¼ 0 using a paired t-test on the square root transformed variables.
3Estimated using the square root transformed value for fruit and vegetable intake and then back-transformed.
4Pearson correlation coefficients deattenuated using a measurement error model.
5Sample sizes for SC analyses are: URI men ¼ 36, women ¼ 87, IIT/Rush men ¼ 42, Emory women ¼ 112.
6SC data not collected.
7Sample size is too small to generate a stable estimate of the correlation in Emory men.
Pearson correlation coefficients by site and gender
between 24HR1and the NCI FVS scored by
alternative scoring methods: frequency alone
(FVS-frequency) and regression estimated serving
size (FVS-estimate) as well as the 1-item
Screener (n ¼ 519)2
Siten Correlation (SE)nCorrelation (SE)
50 0.30 (0.15)
*P , 0.05; **P , 0.01; ***P , 0.001.
1Pearson correlation coefficients deattenuated using a measurement error model.
2Only subjects completing both FVS and 1-item are included. IIT/Rush did not admin-
ister the 1-item, which is the primary reason the sample size is reduced, especially
3The HSPH sample was restricted to women.
4Sample size is too small to generate a stable estimate of the correlation in Emory men.
Evaluation of the NCI Fruit and Vegetable Screener 203S
by guest on December 30, 2011
Correlations between 24HR intake and FVS in women were Download full-text
similar to previous findings, but the FVS produced higher
correlations than alternative methods, in contrast to Thompson
(12). For men, correlations of the FVS with 24HR were lower
than those found by Thompson (12); correlations with alterna-
tive scoring methods and the 1-item were too low to be useful for
Servings of FV as estimated by 24HR showed modest to
moderate correlations with SC for both genders, as has been
found previously (25); however, correlations between FVS and
SC were moderate among women and low and nonsignificant in
men. Future research is recommended before using the FVS to
estimate dietary carotenoid intake in men. In women, correla-
tions between the FVS and SC were higher than correlations
between SC and other scoring methods or 1-item, indicating that
portion size adjustment may be useful.
In summary, in these diverse study populations, the FVS did
not perform as well as in prior cross-sectional studies. One rea-
son may be that BCC participants were recruited into behavioral
intervention studies as opposed to surveillance studies. It is
unknown how generalizable the results of our study are to other
intervention studies, especially given the wide variation in in-
strument correspondence among sites. This study found that
participants overestimated intakes with the FVS, sometimes
substantially, suggesting a positive bias. Correlations between
the FVS and 24HR intake and between the FVS and SC were low
among men, although they were moderate among women.
Overall, obtaining portion size estimates from respondents
seemed to improve correlations with 24HR, although the addi-
tional self-reported information also appeared to exacerbate
tendencies to overestimate. Utility of the instrument for de-
tecting change in intake during the course of intervention studies
is addressed elsewhere in this supplement (26).
The authors acknowledge Susan Schembre for help in prepa-
ration of the manuscript, Susan Rossi, Priscilla Goldstein, Judy
Salkeld, and Milena Anatchkova, for technical assistance and
expertise in building the database and developing analytical
1. Hung HC, Joshipura KJ, Jiang R, Hu FB, Hunter D, Smith-Warner SA,
Colditz GA, Rosner B, Spiegelman D, Willett WC. Fruit and vegetable
intake and risk of major chronic disease. J Natl Cancer Inst. 2004;
US Dept of Health and Human Services, US Dept. of Agriculture, US
Dietary Guidelines Advisory Committee. Dietary guidelines for Amer-
icans, 2005. 6th ed. Washington, DC: GPO; 2005.
US Dept of Health and Human Services. Healthy people 2010.
Washington, DC: US Dept of Health and Human Services, US GPO,
Supt of Documents; 2000.
US Dept of Agriculture, US Dept of Health and Human Services.
Nutrition and your health: Dietary guidelines for Americans. 5th ed.
Washington, DC: US Dept of Agriculture, US Dept of Health and
Human Services; 2000.
Potter J, Finnegan J, Guinard JX, Huerta E, Kelder SH, Kristal A,
Kumanyika S, Li R, Motsinger B, et al. 5 A Day for Better Health
Program evaluation report. Bethesda, MD: National Institutes of
Health, National Cancer Institute; 2000.
Cook A, Friday J. CNRG table set 3.0: pyramid servings intakes in the
United States 1999–2002, 1 day. World Wide Web; 2005.
Thompson FE, Subar A. Dietary assessment methodology. In Coulston
AM, Rock CL, Monsen ER, eds. Nutrition in the prevention and
treatment of disease. San Diego, CA: Academic Press; 2001.
8.Bowen PE, Garg V, Stacewicz-Sapuntzakis M, Yelton L, Schreiner RS.
Variability of serum carotenoids in response to controlled diets con-
taining six servings of fruits and vegetables per day. Ann NY Acad Sci.
Potischman N. Biologic and methodologic issues for nutritional
biomarkers. J Nutr. 2003;133: Suppl 3:875S–80S.
10. Mayne ST, Cartmel B, Silva F, Kim CS, Fallon BG, Briskin K, Zheng T,
Baum M, Shor-Posner G, Goodwin WJ Jr. Plasma lycopene concentra-
tions in humans are determined by lycopene intake, plasma cholesterol
concentrations and selected demographic factors. J Nutr. 1999;129:
11. Thompson FE, Kipnis V, Subar AF, Krebs-Smith SM, Kahle LL,
Midthune D, Potischman N, Schatzkin A. Evaluation of 2 brief instru-
ments and a food-frequency questionnaire to estimate daily number of
servings of fruit and vegetables. Am J Clin Nutr. 2000;71:1503–10.
12. Thompson FE, Subar AF, Smith AF, Midthune D, Radimer KL, Kahle
LL, Kipnis V. Fruit and vegetable assessment: performance of 2 new
short instruments and a food frequency questionnaire. J Am Diet Assoc.
13. Thompson FE, Midthune D, Subar AF, Kahle LL, Schatzkin A, Kipnis V.
Performance of a short tool to assess dietary intakes of fruits and
vegetables, percentage energy from fat and fibre. Public Health Nutr.
14. Thompson FE, Midthune D, Subar AF, McNeel T, Berrigan D, Kipnis V.
Dietary intake estimates in the National Health Interview Survey, 2000:
methodology, results, and interpretation. J Am Diet Assoc. 2005;105:
15. Yaroch AL, Nebeling L, Thompson FE, Hurley TG, Hebert JR, Toobert
DJ, Resnicow K, Greene GW, Elliot DL, et al. Baseline design elements
and sample characteristics for seven sites participating in the Nutrition
Working Group of the Behavior Change Consortium. J Nutr. 2008;138:
16. US Dept of Agriculture Center for Nutrition Policy and Promotion. The
food guide pyramid. Home and garden bulletin No. 252. Washington,
DC: USDA; 1996.
17. Laforge RG, Greene GW, Prochaska JO. Psychosocial factors influencing
low fruit and vegetable consumption. J Behav Med. 1994;17:361–74.
18. Resnicow K, Odom E, Wang T, Dudley WN, Mitchell D, Vaughan R,
Jackson A, Baranowski T. Validation of three food frequency question-
naires and 24-hour recalls with serum carotenoid levels in a sample of
African-American adults. Am J Epidemiol. 2000;152:1072–80.
19. Stacewicz-Sapuntzakis M, Bowen P, Kikendall J, Burgess M. Simulta-
neous determination of serum retinol and various carotenoids: their
distribution in middle-aged men and women. J Micronutr Anal. 1987;
20. Potischman N, Herrero R, Brinton LA, Reeves WC, Stacewicz-
Sapuntzakis M, Jones CJ, Brenes MM, Tenorio F, de Britton RC,
Gaitan E. A case-control study of nutrient status and invasive cervical
cancer. II. Serologic indicators. Am J Epidemiol. 1991;134:1347–55.
21. Duewer DL, Kline MC, Sharpless KE, Thomas JB, Stacewicz-
Sapuntzakis M, Sowell AL. NIST micronutrients measurement quality
assurance program: characterizing individual participant measurement
performance over time. Anal Chem. 2000;72:3611–9.
22. Freedman LS, Carroll RJ, Wax Y. Estimating the relation between
dietary intake obtained from a food frequency questionnaire and true
average intake. Am J Epidemiol. 1991;134:310–20.
23. Hebert JR, Hurley TG, Hsieh J, Rogers E, Stoddard AM, Sorensen G,
Nicolosi RJ. Determinants of plasma vitamins and lipids: the Working
Well Study. Am J Epidemiol. 1994;140:132–47.
24. Resnicow K, Jackson, A, Blissett D, Wang T, McCarty F, Rahotep S,
Periasamy S. Results of the Healthy Body Healthy Spirit Trial. Health
25. Boeing H, Bohlscheid-Thomas S, Voss S, Schneeweiss S, Wahrendorf J.
The relative validity of vitamin intakes derived from a food frequency
questionnaire compared to 24-hour recalls and biological measure-
ments: results from the EPIC pilot study in Germany. European Pros-
pective Investigation into Cancer and Nutrition. Int J Epidemiol. 1997;26:
26. Peterson KE, Hebert JR, Hurley TG, Resnicow K, Thompson FE,
Greene GW, Shaikh AR, Yaroch AL, Williams GC, Salkeld J, et al.
Accuracy and precision of two short screeners to assess change in fruit
and vegetable consumption among diverse populations participating in
health promotion intervention trials. J Nutr. 2008;138:218S–225S.
by guest on December 30, 2011