Free fruit at workplace intervention increases total fruit intake: a validation study using 24 h dietary recall and urinary flavonoid excretion

Abstract

Background/Objectives:

To validate 24 h dietary recall of fruit intake by measuring the total 24 h excretion of 10 different flavonoids in 24 h urine during an intervention with free fruit at workplaces.

Subjects/Methods:

Employees at workplaces offering a free-fruit program, consisting of daily free and easy access to fresh fruit, and controls employees at workplaces with no free-fruit program were enrolled in this validation study (n=103). Dietary intake was assessed by using a 24 h dietary recall questionnaire at baseline and approximately 5 months later. Ten flavonoids, quercetin, isorhamnetin, tamarixetin, kaempferol, hesperetin, naringenin, eriodictyol, daidzein, genistein, and phloretin, were measured using HPLC–electrospray ionization–MS.

Results:

The 24 h urinary excretion of total flavonoids and the estimated intake of fruits were significantly correlated (rs=0.31, P<0.01). The dietary intake of citrus fruits and citrus juices was significantly correlated with total excretion of citrus specific flavonoids (rs=0.28, P<0.01), and orange was positively correlated with naringenin (rs=0.24, P<0.01) and hesperetin (rs=0.24, P<0.01). Phloretin in urine was correlated with apple intake (rs=0.22, P<0.01) and also with overall estimated intake of fruit (rs=0.22, P<0.01).

Conclusions:

This study shows that a 24 h dietary recall can be used as a valid estimate of the intake of fruits in agreement with an objective biomarker of fruit intake in free fruit at workplace interventions.

Introduction

Meta-analyses of observational studies have repeatedly shown that a high fruit and vegetable intake is associated with a reduced risk of cardiovascular disease, even though causality and mechanism remain to be shown (Riboli and Norat, 2003; Dauchet et al., 2006; He et al., 2007; Duijnhoven et al., 2009). On the basis of these results, authorized food-based dietary guidelines recommend to eat more fruits and vegetables, for example the ‘5–10 a day’ program in Canada, the ‘go for 2&5’ program in Australia or the ‘6 a day’ program in Denmark. Fruit and vegetable intake is, however, still inadequate among the majority of the population in many countries (Ashfield-Watt et al., 2004; Lassen et al., 2004; Guenther et al., 2006; Ovesen et al., 2007; Kimmons et al., 2009). The average intake of fruits and vegetables in Denmark is currently 434 g/day with only 16% of the population consuming an amount, corresponding to the Danish recommendations of 600 g fruits and vegetables per day for adults and children above 10 years old (Astrup et al., 2005; Fagt et al., 2008).

It has been shown that simple provision of information is not enough to achieve significant changes in the dietary behavior of a population (Eertmans et al., 2001; Stockley, 2001). Free-fruit campaigns on worksites are, therefore, well suited as an environmental strategy with the potential for increasing the daily fruit intake in a given population. This study will investigate whether a 24 h dietary recall is a valid tool to measure if a free-fruit intervention at workplace will increase fruit intake among employees.

Estimation of fruit and vegetable intake is complicated by a tendency to over-report intake of healthy foods (Gibson, 1990). Furthermore, food registration methods are often based on self-reported data, which implies the risk for subjective bias (Kipnis et al., 2001). Biological markers of exposure as an alternative to the more traditional dietary assessment tools have been used for many years to provide semi-quantitative indexes of the exposure to individual food constituents or food groups such as fruits or vegetables (Spencer et al., 2008). A combination of several different flavonoids quantified in 24 h urine samples has recently been shown to correlate more strongly to fruit intake than plasma carotenoids. Therefore, at the present, a combination of urinary flavonoids seems to be the best performing objective biomarker of fruit intake (Nielsen et al., 2002; Brantsæter et al., 2007; Mikkelsen et al., 2007). This biomarker has, therefore, been used in a workplace-based intervention study providing free fruit or no free fruit to employees as validation of a 24 h dietary recall.

Materials and methods

Workplaces and subjects

Eight comparable workplaces in the Copenhagen area signed up for the study. Five were enrolled as intervention workplaces and the remaining three workplaces, without any actual consideration of free fruit at the workplace, were enrolled as control workplaces. At each workplace, collaboration with a contact person was established. Recruitment of the employees, interested in participating in the study, occurred through this contact. Altogether, 146 employees were enrolled at baseline in the free fruit at work intervention study. Of the 146 employees, a total of 103 accepted participation in the validation study. Pregnant and lactating women, and individuals, not expecting to be at the particular workplace 5 months later were excluded. The study protocol was accepted by the Ethics Committee of the Copenhagen and Frederiksberg municipalities (J. No. KA-20060047).

The intervention

Workplaces entered the study at distinct points in time, starting between June and September 2006. Assessments were made both at baseline and at termination approximately 5 months later. The intervention was a fruit program, consisting of a fruit basket placed where employees had free and easy access, that is in the reception or in a kitchenette. There was at least one piece of fruit per employee each day. The fruit intervention was not accompanied with informational, counselling or other health promotion activities to make a minimal difference to the controls.

Dietary assessment

Dietary intake was assessed by a 24 h dietary recall questionnaire, which was a modified form of the dietary recall questionnaire from the Danish National Dietary Survey 2000–2002 (Lyhne et al., 2005). The recall was performed by trained interviewers both at baseline and after 5 months. The software program, General Intake Estimion System (version 1.0, Technical University of Denmark, National Food Institute, Division of Nutrition, 2008), was used to calculate dietary intake.

Urine samples

Urine samples were collected by the employees through 24 h at baseline and 5 months later to determine the concentration of flavonoids as an objective biomarker for fruit intake. The collection of the 24 h urine samples started in the morning the day before completion of the 24 h recall questionnaires and lasted until the next day at the same hour. Hence, the 24 h urine sample and the 24 h dietary recall questionnaire covered the same period of time. All urine samples were collected as previously described by Krogholm et al. (2004). The employees were instructed on how to collect the urine and in the importance of providing complete samples. Completeness of the urine collection was checked by oral questionnaires and study diaries. Anthropometric measurements (height, bodyweight, and waist circumference) were also performed, and will be published elsewhere.

Determination of urinary flavonoids

The flavonoids were determined by LC–MS after enzymatic hydrolysis of conjugates, as described by Nielsen et al. (2000) with slight modifications. In short, 2 ml aliquots of each urine sample were initially added 500 ng of 13C O-desmethylangolensin internal standard (20 ng/μl dimethylsulfoxid) and enzymatically hydrolyzed. The hydrolyzed samples were evaporated to dryness under vacuum. The urine samples were then dissolved with 50 μl 100% methanol and 2.0 ml 0.5% formic acid and added on an Isolute SPE 100 column preconditioned with 2.0 ml 100% methanol and 2.0 ml 0.5% formic acid. The column was washed and the flavonoids eluted and evaporated as described in Nielsen et al. (2000). After evaporation, the samples were redissolved in 25 μl 100% methanol and 200 μl 0.5% formic acid and added 500 ng of 13C-daidzein as an additional standard (20 ng/μl dimethylsulfoxid). The entire amount of supernatant was injected into the LC–MS system.

Reagents and standards

Enzymes used for the hydrolysis of the flavonoid glycosides in urine samples were arylsulfatase (Aerobacter aerogenes, 16.8 standard units/ml) from Sigma Chemicals Co. (St Louis, MO, USA) and β-glucoronidase (Escherichia coli, >200 standard units/ml) obtained from Boehringer Mannheim (Mannheim, Germany). Methanol and acetonitrile were of HPLC grade and obtained from Rathburne Ltd. (Walkerburn, UK). The flavonoid standards quercetin, kaempferol, isorhamnetin, tamarixetin, and naringenin were obtained from Aldrich (Steinheim, Germany). Hesperetin, eriodictyol, and phloretin were purchased from Sigma Chemicals Co. Genistein and daidzein were obtained from LC Laboratories (Woburn, MA, USA). The isotopically labeled internal standards, 3 × 13C O-desmethylangolensin, and 3 × 13C-daidzein were obtained from School of Chemistry, University of St Andrews, UK. Dimethylsulfoxid (Urasol) was purchased from Merck & Co., Inc. (Whitehouse Station, NJ, USA). The Isolute SPE 100 was purchased from Mikrolab, Aarhus, Denmark. All standards were HPLC grade. The concentration of flavonoids in urine samples were determined as single determinations based on calibration curves generated by spiked blank urine samples as described by Nielsen et al. (2000).

Statistical analysis

The concentration of flavonoids in urine and intake of fruit and flavonoid-rich foods did not have a normal distribution even after logarithmic transformation, so nonparametric tests were used in the statistical analysis of the data. Wilcoxon's two-related samples test were performed in the intervention (n=34) and control (n=45) group separately to evaluate changes from baseline to after 5 months in the urinary excretion of flavonoids, in intakes of fruit, and individual flavonoid-rich foods. The Mann–Whitney U-tests were performed to compare the two groups (control and intervention) on one variable at the time. Spearman's correlation (rs) was used to examine associations between the intake of fruits, flavonoid-rich foods, and the excretion of the flavonoid biomarkers in urine (n=158). The analyses were made using the SPSS package program version 14.0 (SPSS, Inc., Chicago, IL, USA). P-values <0.05 (two tailed) were regarded as statistically significant.

Results

Participants and food intake

Altogether, 103 employees were enrolled at baseline in the validation study. Of these, 99 employees did complete the 24 h dietary recall and 24 h urine collection at baseline. At the second measurement, after 5 months, the 24 h dietary recall and the collection of 24 h urine sample was completed by 79 out of the 99 employees. Main causes of drop out or exclusion were unexpected termination of employment (16 individuals) and incomplete 24 h urine collection. Data from the 79 employees were analyzed using Wilcoxon's two-related samples test and the Mann–Whitney U-tests.

At baseline, there were no significant differences between the control and intervention groups in the estimated dietary intakes of fruits, citrus fruits and citrus juices, vegetables, fruits and vegetables, apples, and oranges based on 24 h dietary recall questionnaires (see Table 1). After 5 months of intervention, the total intake of fruits was higher in the group with free access to fruit at work every day, compared with the control group receiving no additional fruit (median 310 (15, 1312) g/day vs median 265 (0, 732) g/day, P<0.01) (see Figure 1). In addition, the overall change in fruit intake from baseline to after 5 months was significantly higher in the intervention group (median 72 (310, 792) g/day, P<0.01) compared with the control group (median 2 (−308, 490) g/day). As seen in Table 1, the median intake of citrus fruits and juices increased from 0 g/day at baseline to 50 g/day after 5 months, and this change in intake in the intervention group was significant higher than in the control group (P<0.05). Moreover, the intake of fruit in the control group tended to increase over the 5 months study period (from median 193 (2, 541) g/day to median 265 (0, 732) g/day), though the change was not statistically significant (see Figure 1).

Table 1 Median (P5, P95) dietary intake estimated by 24 h dietary recall (g/day) and 24 h urinary excretion of flavonoids (μg) in control and intervention group at baseline and after 5 months of a free fruit at workplace campaign
Figure 1
figure1

Error bars reflecting the change over time (from baseline to after 5 months) in the median (95% CI) estimated intake of fruits (g/day) between control and intervention group.

Biomarkers of fruit intake

The median (P5, P95) 24 h urinary excretion of total flavonoids (that is the sum of quercetin, isorhamnetin, tamarixetin, kaempferol, hesperetin, naringenin, eriodictyol, daidzein, genistein, and phloretin) was similar in the control and intervention groups at baseline (median 352 (66, 1506) μg vs median 175 (65, 2569) μg) (see Table 1). After 5 months of free access to fruit at workplace every day, the 24 h urinary excretion of total flavonoids, in the intervention group, had increased significantly from median 175 (65, 2569) μg to median 635 (78, 8262) μg. Moreover, the amount of total citrus flavonoids (that is the sum of hesperetin, naringenin, and eriodictyol) increased significantly after 5 months in the intervention group (P<0.05). In the control group, the urinary excretion of total flavonoids and total citrus flavonoids was also increased significantly after 5 months (P<0.05) (see Table 1).

The quantitatively largest amounts of flavonoids excreted in urine were the citrus flavonoids hesperetin, naringenin, and eriodictyol (see Table 1). Kaempferol, phloretin, quercetin, genistein, daidzein, isorhamnetin, and tamarixetin were excreted in lower amounts and did not change significantly in any of the two groups over time (data not shown).

Correlations

In this study, we use the Spearman's correlations coefficients for validation of the self-reported fruit intake. Spearman's correlations were calculated for the employees with complete 24 h dietary recall and 24 h urine collection at both baseline and after 5 months, corresponding to a total of 158 employees. Spearman's correlations between dietary intake estimated by 24 h dietary recall and 24 h urinary excretion of different combinations of flavonoids showed that total flavonoids in urine was highly and significantly correlated (rs=0.31, P<0.01, n=158) with the total intake of fruits (see Table 2). Adding the intake of vegetables to the fruit intake did make the strength of the Spearman's correlation even stronger to total flavonoids in urine (rs=0.37, P<0.01). Urinary excretion of the combination of hesperetin, naringenin, phloretin, and eriodictyol (referred to as the ‘fruit marker’), all present in fruits or formed after fruit consumption, were also positively correlated to intake of fruits (rs=0.29, P<0.01), but the correlation was stronger when including the isoflavonids, genistein, and daidzein, and the flavonols quercetin, kaempferol, isorhamnetin, and tamarixetin, which all are present in both fruits and vegetables (rs=0.31, P<0.01) (see Table 2). Correlations between excretion of specific flavonoids and intake of particular foods were studied based on their known occurrence in these foods. The dietary intake of citrus fruits and citrus juices was significantly correlated with total citrus flavonoids (rs=0.24, P<0.01), and oranges were positively correlated with naringenin (rs=0.24, P<0.01) and hesperetin (rs=0.24, P<0.01). Furthermore, the total citrus flavonoids were significantly correlated to the intake of fruits in general (rs=0.28, P<0.01). Phloretin in urine was correlated with apple intake (rs=0.22, P<0.01) and also with overall estimated intake of fruit (rs=0.22, P<0.01). Finally, some highly significant correlations between individual flavonoids were observed: urinary excretion of hesperetin was correlated with excretion of naringenin (rs=0.60, P<0.0001) and eriodictyol (rs=0.58, P<0.0001), naringenin with eriodictyol (rs=0.52, P<0.0001) and phloretin (rs=0.23, P<0.001), quercetin with phloretin (rs=0.96, P<0.0001), isorhamnetin (rs=1, P<0.0001) and tamarixetin (rs=1, P<0.0001), and daidzein was correlated with genistein (rs=0.52, P<0.0001).

Table 2 Spearman's correlations (lower 95% confidence interval–upper 95% confidence interval) between intake of fruit and flavonoid-rich foods determined by 24 h dietary recall and 24 h urinary excretion of flavonoids (n=158)

Discussion

In this study, we used the combination of several different flavonoids excreted in 24 h urine as a reference biomarker to the self-reported intake of fruits and flavonoid-rich foods. The link between intake of fruits and vegetables and the urinary excretion of flavonoids has been well established in controlled intervention studies with specific foods (Nielsen et al., 2002; Brevik et al., 2004; Krogholm et al., 2004) and in free-living populations (Nielsen et al., 2002; Brantsæter et al., 2007; Mikkelsen et al., 2007). Therefore, the significant correlation between the urinary total flavonoids and fruit intake in this study shows that the estimation of intake of fruits by the 24 h dietary recall is a valid estimate of the true effect of the free-fruit intervention program. The correlation values and excretion levels in this validation study are in the same range as previously reported (Nielsen et al., 2002; Brevik et al., 2004; Krogholm et al., 2004; Brantsæter et al., 2007; Mikkelsen et al., 2007).

In this study, the quantitatively largest amounts of flavonoids excreted in urine were the citrus flavonoids (hesperetin, naringenin, and eriodictyol). The main reasons for this is that the urinary excretion relative to the intake of the citrus flavonoids, hesperetin, and naringenin is roughly 10 times higher than for the flavonols (Manach et al., 2005; Krogholm et al., 2010). Owing to the high relative urinary excretion of citrus flavonoids, citrus fruit and citrus juice intake is more easily reflected by our flavonoid biomarker than the fruits containing only flavonols. This was for instance seen in this study as highly significant correlations between intake of citrus fruits and citrus juices and total citrus flavonoids. Moreover, the previously reported high correlation between phloretin in urine and intake of apples (Mennen et al. 2006; Brantsæter et al., 2007) was confirmed in this study (rs=0.22, P<0.01). Urinary phloretin was also correlated with overall estimated intake of fruits (rs=0.22, P<0.01), indicating that individuals consuming apples are ‘high fruit consumers’ in general. We could only observe weak correlations between the 24 h urinary excretion of quercetin (rs=0.17, P<0.05) and intake of apple, including apple juice. Phloretin, therefore, appears to be a better biomarker for apple intake than quercetin, even though apples are also a dietary important source of quercetin. Ito et al. (2005) has suggested that phloretin is a metabolite of naringenin formed by reductive opening of the heterocyclic C-ring, and Mennen et al. (2006) has found high correlations between phloretin and naringenin (rs=0.51, P<0.0001). In this study, the correlation between phloretin and naringenin was also significant (rs=0.23, P<0.01), although the association was weaker than in the study by Mennen et al. (2006).

Although the citrus flavonoids are dominating among the flavonoids measured in our biomarker, this study consolidates the importance of including several different flavonoids and/or metabolites when using flavonoids as an overall biomarker for intake of fruits, as the combination of all the flavonoids measured in this study result in the strongest correlation to estimated intake of fruits (rs=0.31, P<0.01), with a 95% confidence interval from 0.16 to 0.45, which is acceptable when validation is the overall purpose. Adding more flavonoids and/or flavonoid metabolites present in fruits might further improve the accuracy of the flavonoid biomarker. Further research investigating this is needed. The magnitude of a given correlation between a biomarker and self-reported food intakes cannot be expected to be very high even if both methods are quite accurate, and there is at present no agreement in literature as to what constitutes a satisfactory level of correlation. The magnitude of the presented correlations between total flavonoid in urine and the estimated dietary intake of fruits, fruits and vegetables, and citrus fruits and citrus juices, given the relatively small sample size and the rather narrow range in dietary intake in this study, is rather high.

Being in a distinct protocol can result in changes in lifestyle and exercise, also referred to as the placebo effect. In this study, this was reflected by an increased fruit intake in both the control and intervention group because volunteers in both groups were informed about the purpose of the study. Over the 5 months study period, the intake of fruits in the control group changed from median 193 (2, 541) g/day to median 265 (9, 732) g/day. According to the 24 h dietary recall, this increase was not significant, whereas the urinary total flavonoid responded significantly to this change in intake. This could indicate that the 24 h dietary recall is less sensitive as a marker of fruit intake than our flavonoid biomarker. With a larger sample size, the power would increase and the 24 h dietary recall would then be a cheap and apparently accurate marker of fruit intake. In conclusion, this study shows highly significant correlations between intake of fruit, estimated by 24 h dietary recall, and the reference biomarker for fruit intake, the 24 h urinary excretion of total flavonoids.

References

  1. Ashfield-Watt PA, Welch AA, Day NE, Bingham SA (2004). Is ‘five-a-day’ an effective way of increasing fruit and vegetable intakes? Public Health Nutr 7, 257–261.

    CAS  Article  Google Scholar 

  2. Astrup A, Andersen NL, Stender S, Trolle E (2005). Kostrådene 2005. Copenhagen, Ernæringsrådet og Danmarks Fødevareforskning. 9-8-2007.

  3. Brantsæter AL, Haugen M, Rasmussen SE, Alexander J, Samuelsen AO, Meltzer HM (2007). Urine flavonoids and plasma carotenoids in the validation of fruit, vegetable and tea intake during pregnancy in the Norwegian Mother and Child Cohort Study (MoBa). Public Health Nutr 10, 838–847.

    Article  Google Scholar 

  4. Brevik A, Rasmussen SE, Drevon CA, Andersen LF (2004). Urinary excretion of flavonoids reflect even small changes in the dietary intake of fruits and vegetables. CEBP 13, 843–848.

    CAS  Google Scholar 

  5. Dauchet L, Amouyel P, Hercberg S, Dallongeville J (2006). Fruit and vegetable consumption and risk of coronary heart disease: a meta-analysis of cohort studies. J Nutr 136, 2588–2593.

    CAS  Article  Google Scholar 

  6. Duijnhoven FJB, Mesquita HBB De, Ferrari P, Jenab M, Boshuizen HC, Ros MM et al. (2009). Fruit, vegetables, and colorectal cancer risk: the European prospective investigation into cancer and nutrition. Am J Clin Nutr 89, 1441–1452.

    Article  Google Scholar 

  7. Eertmans A, Baeyens F, Van den Bergh O (2001). Food likes and their relative importance in human eating behaviour: review and preliminary suggestions for health promotion. Health Educ Res 16, 443–456.

    CAS  Article  Google Scholar 

  8. Fagt S, Biltoft-Jensen A, Matthiessen J, Groth MV, Christensen T, Trolle E (2008). Dietary habits of Denmark 1995–2006 Status and development with focus on fruits, vegetables and added sugar. Report, ISBN: 978-87-92158-19-2, Department of Nutrition, National Food Institute, Technical University of Denmark.

  9. Gibson RS (1990). Principles of Nutritional Assessment. Oxford University Press: Oxford, UK.

    Google Scholar 

  10. Guenther PM, Dodd KW, Reedy J, Krebs-Smith SM (2006). Most Americans eat much less than recommended amounts of fruits and vegetables. J Am Diet Assoc 106, 1371–1379.

    Article  Google Scholar 

  11. He FJ, Nowson CA, Lucas M, MacGregor GA (2007). Increased consumption of fruit and vegetables is related to a reduced risk of coronary heart disease: meta-analysis of cohort studies. J Hum Hypertens 21, 717–728.

    CAS  Article  Google Scholar 

  12. Ito H, Gonthier MP, Manach C, Morand C, Mennen L, Rémésy C et al. (2005). Polyphenol levels in human urine after intake of six different polyphenol-rich beverages. Br J Nutr 94, 500–509.

    CAS  Article  Google Scholar 

  13. Kipnis V, Midthune D, Freedman LS, Bingham S, Schatzkin A, Subar A et al. (2001). Empirical evidence of correlated biases in dietary assessment instruments and its implications. Am J Epidemiol 153, 394–403.

    CAS  Article  Google Scholar 

  14. Krogholm KS, Bredsdorff L, Knuthsen P, Haraldsdóttir J, Rasmussen SE (2010). Relative bioavailability of the flavonoids quercetin, hesperetin and naringenin given simultaneously through diet. EJCN 64, 432–435.

    CAS  PubMed  Google Scholar 

  15. Krogholm KS, Haraldsdottir J, Knuthsen P, Rasmussen SE (2004). Urinary total flavonoid excretion but not 4-pyridoxic acid or potassium can be used as a biomarker for the intake of fruits and vegetables. J Nutr 134, 445–451.

    CAS  Article  Google Scholar 

  16. Kimmons J, Gillespie C, Seymour J, Serdula M, Blanck HM (2009). Fruit and vegetable intake among adolescents and adults in the United States: percentage meeting individualized recommendations. J Med 11, 26.

    Google Scholar 

  17. Lassen A, Thorsen AV, Trolle E, Elsig M, Ovesen L (2004). Successful strategies to increase the consumption of fruits and vegetables: results from the Danish ‘6 a day’ Work-site Canteen Model Study. Publich Health Nutr 7, 263–270.

    Google Scholar 

  18. Lyhne N, Christensen T, Groth MV, Fagt S, Biltoft-Jensen A, Hartkopp HB et al. (2005). Dietary Habits in Denmark 2000–2002 Main Results. Danish Institute for Food and Veterinary Research: Soeborg.

    Google Scholar 

  19. Manach C, Williamson G, Morand C, Scalbert A, Remesy C (2005). Bioavailability and bioefficacy of polyphenols in humans. I. Review of 97 bioavailability studies. Am J Clin Nutr 81, 230S–242S.

    CAS  Article  Google Scholar 

  20. Mennen LI, Sapinho D, Ito H, Bertrais S, Galan P, Hercberg S et al. (2006). Urinary flavonoids and phenolic acids as biomarkers of intake for polyphenol-rich foods. Br J Nutr 96, 191–198.

    CAS  Article  Google Scholar 

  21. Mikkelsen TB, Olsen SF, Rasmussen SE, Osler M (2007). Relative validity of fruit and vegetable intake estimated by the food frequency questionnaire used in the Danish National Birth Cohort. Scand J Public Health 35, 172–179.

    Article  Google Scholar 

  22. Nielsen SE, Freese R, Cornett C, Dragsted LO (2000). Identification and quantification of flavonoids in human urine samples by column-switching liquid chromatography coupled to atmospheric pressure chemical ionization mass spectrometry. Anal Chem 72, 1503–1509.

    CAS  Article  Google Scholar 

  23. Nielsen SE, Freese R, Kleemola P, Mutanen M (2002). Flavonoids in human urine as biomarkers for intake of fruits and vegetables. CEBP 11, 459–466.

    CAS  Google Scholar 

  24. Ovesen L, Andersen NL, Dragsted LO, Hodtfredsen J, Haraldsdóttir J, Stender K et al. (2007). Frugt, grønt og helbred—Opdatering af vidensgrundlaget (2002). Report, ISBN: 87-91189-60-8, Ministeriet for fødevare, landbrug og fiskeri, fødevaredirektoratet, copenhagen, Denmark.

  25. Riboli E, Norat T (2003). Epidemiologic evidence of the protective effect of fruit and vegetables on cancer risk. Am J Clin Nutr 78 (Suppl), 559S–569S.

    CAS  Article  Google Scholar 

  26. Stockley L (2001). Toward public health nutrition strategies in the European Union to implement food based dietary guidelines and to enhance healthier lifestyles. Public Health Nutr 4 (2A), 307–324.

    CAS  PubMed  Google Scholar 

  27. Spencer JPE, El Mohsen MMA, Minihane AM, Mathers JC (2008). Biomarkers of the intake of dietary polyphenols: strengths, limitations and applications in nutrition research. Br J Nutr 99, 12–22.

    CAS  Article  Google Scholar 

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Acknowledgements

This study is part of the ISAFRUIT project, funded by the European commission under the Thematic Priority 5-Food Quality and Safety of the 6th framework Program of RTD (Contract no. FP6-FOOD–CT-2006-016279). The views and opinions expressed in this publication are purely those of the writers and may not in any circumstances be regarded as stating an official position of the European Commission. We are grateful to the employees who participated in this study for the dedication to this study. Furthermore, we thank Anni Schou for the skilful technical assistance.

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Correspondence to K S Krogholm.

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Contributors: KSK contributed to the study design, carried out the study, was responsible for statistical calculations, interpreted the data, and wrote the manuscript; LB was responsible for determination of flavonoids in urine by LC–MS, contributed to manuscript editing, and carried out the study; SA carried out the study and contributed to manuscript editing; TC calculated the dietary intake and contributed to manuscript editing; SER contributed to study design and manuscript editing; LOD was responsible for study design and contributed to manuscript editing.

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Krogholm, K., Bredsdorff, L., Alinia, S. et al. Free fruit at workplace intervention increases total fruit intake: a validation study using 24 h dietary recall and urinary flavonoid excretion. Eur J Clin Nutr 64, 1222–1228 (2010). https://doi.org/10.1038/ejcn.2010.130

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Keywords

  • validation
  • fruit
  • vegetables
  • biomarker
  • flavonoids
  • 24 h dietary recall

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