In nutrition research and clinical settings, short FFQ are powerful tools for estimating dietary exposures of interest and assessing the associated risks. There is emerging interest in the potential health benefits of marine product intake, with evidence of a protective role in CVD(Reference Kris-Etherton, Harris and Appel1), depression(Reference Freeman, Hibbeln and Wisner2) and inflammatory disorders such as rheumatoid arthritis(Reference Calder3). Two long-chain (LC) n-3 (omega-3) PUFA – EPA (20 : 5n-3) and DHA (22 : 6n-3) – have been proposed as being responsible for the beneficial effects of marine food products intake(Reference Mozaffarian and Rimm4). The measurement of nutritional biomarkers such as fatty acids (FA) in blood (plasma, red blood cells (RBC), etc.) offers a validation tool that has some advantages(Reference Arab5). Such biomarkers of FA intake provide quantitative measurements independently of memory and/or knowledge of the subjects and are less likely to be due to social desirability bias and errors in completion than dietary self-reporting(Reference Bates and Thurnham6–Reference Hebert, Ma, Clemow, Ockene, Saperia, Stanek, Mérriam and Ockene9).
Since LC n-3 PUFA cannot be synthesized de novo in the human body, they are known as essential FA and must come from the diet(Reference Holman10). Therefore, n-3 represent ideal FA for validation(Reference Willett7). Although man is technically capable of endogenously synthesizing EPA and DHA from the n-3 precursor α-linolenic acid (α-LNA, 18 : 3n-3) found in plants, this conversion is very limited(Reference Plourde and Cunnane11). Therefore, in general, EPA and DHA concentrations in blood reflect habitual dietary n-3 FA intake from fish(Reference Arab5). For this reason, several studies have used EPA and DHA biomarkers to validate dietary EPA and DHA intake measured by FFQ(Reference Sun, Ma, Campos, Hankinson and Hu12–Reference Baylin, Kim, Donovan-Palmer, Siles, Dougherty, Tocco and Campos19) and dietary records(Reference Broadfield, McKeever, Fogarty and Britton20–Reference Kuriki, Nagaya and Tokudome22). The present manuscript evaluates the validity of a simple FFQ for the assessment of dietary EPA and DHA against their relative concentrations in RBC.
Methods
Subjects
Baseline data of middle-aged women involved in a clinical trial were taken for validation of our FFQ. This randomized clinical trial has been described in detail elsewhere(Reference Lucas, Asselin, Mérette, Poulin and Dodin23). Briefly, its aim was to compare the effects of enriched ethyl-EPA supplementation with placebo for the treatment of psychological distress and depressive symptoms. Women with low marine food product intakes (<3 servings/week) were recruited from the general population and were considered for participation if they were between 40 and 55 years of age and had moderate to severe psychological distress, defined as a score of ≤72 on the Psychological General Well-Being Schedule(Reference Dupuy24). Exclusion criteria were: past or current history of schizophrenia or bipolar I and II disorders; current or significant imminent risk of suicide or homicide; being postmenopausal for more than 5 years; endocrine diseases and medical disorders known to affect mental health; current substance abuse or dependence; fish allergies; taking antidepressants, hormone replacement therapy, St. John’s wort (Hypericum perforatum) or fish oil supplements in the last 3 months before enrolment; and the use of anticoagulants.
A total of 120 women were randomized and allocated to treatments. It has been postulated that n-3 FA deficiency among major depressed people could be due to genetically impaired FA and phospholipid metabolism(Reference Ross25, Reference Horrobin and Bennett26). Therefore, we excluded from the present FFQ analysis women who had a baseline diagnosis of major depression episodes (n 29), minor depression (n 15) or dysthemia (n 2) according to criteria of the Diagnostic and Statistical Manual of Mental Disorders, fourth edition. Moreover, nine women had missing RBC FA measurement. The final sample size analysed was sixty-five.
Design and procedures
Interviews and questionnaires were administered at the Centre Menopause Québec of Saint-François d’Assise Hospital. All women signed an informed consent form after a full review of the inclusion and exclusion criteria and the risks and benefits of the study, which was approved by the Saint-François d’Assise Hospital Ethics and Clinical Research Board. A full medical history and semi-structured psychiatric evaluation were undertaken by clinic psychiatrists.
The FFQ
The FFQ had two principal questions. The first question referred to the portion size of fish consumed: ‘In general, what is the portion size that corresponds best to your habitual consumption when you eat fish?’ Each response had six predefined categories: ‘85 g (3 oz), i.e. a size equivalent to a regular deck of playing cards’; ‘113 g (4 oz), i.e. about 1½ times the size of a deck of cards’; ‘170 g (6 oz), i.e. 2 times the size of a deck of cards’; ‘227 g (8 oz), i.e. about 2½ times the size of a deck of cards’; ‘never eat marine food products’; or ‘don’t know/refuse to answer’. The latter two categories were not offered to respondents but were noted if they provided these answers. A fixed portion of 85 g or 3 oz was assigned for molluscs, crustaceans and imitation crab. The second question of the FFQ was aimed at knowing the frequency of marine food products consumed: ‘Based on your food consumption of the last month, how many times did you consume the following marine food products?’ Each response had eight pre-defined categories: ‘never’, ‘once a month’, ‘2–3 times per month’, ‘once a week’, ‘2–3 times per week’, ‘4–6 times per week’, ‘once a day’ or ‘don’t know/refuse to answer’. These categories were converted to daily consumption frequency as follows: never = 0, once a month = 1/30·42, 2–3 times per month = 2·5/30·42, once a week = 1/7, 2–3 times per week = 2·5/7, 4–6 times per week = 5/7 and once a day = 1. The questionnaire included seven groups of marine food products: (i) oily fish (fresh or canned salmon, herring, mackerel, sardines); (ii) canned tuna; (iii) trout or halibut; (iv) white fish (sole, rockfish, haddock, cod, etc.); (v) molluscs (mussels, oysters, clams, scallops); (vi) crustaceans (shrimps, crabs, lobsters, etc.); and (vii) imitation crab. Based on the 2005 Canadian Nutrient File of Health Canada(27) (see Appendix), each of these groups of marine food products was assigned an amount of EPA + DHA: 14·9, 3·8, 9·3, 3·4, 4·9, 2·9 and 6·1 mg/g, respectively. An amount of EPA was also assigned to each of these groups: 5·9, 0·9, 3·7, 1·3, 2·4, 1·9 and 2·4 mg/g, respectively. For DHA, amounts assigned to each group were respectively 9·1, 2·8, 5·7, 2·1, 2·5, 1·1 and 3·6 mg/g. The daily intake of each marine food product (g/d) was calculated by multiplying portion size (g) by the frequency of consumption (per d). Thereafter, the daily intakes of EPA and DHA (mg/d) were calculated by multiplying the intake of each marine food product (g/d) by its EPA and DHA concentration (mg/g). Since docosapentaenoic acid (DPA, 22 : 5n-3) measurement was not available from the FA profile of most fish and seafood in the Canadian Nutrient Data File, we were not able to determine DPA concentration in food products assessed by our FFQ.
Determination of red blood cell fatty acid concentrations
The FA composition of RBC membranes was quantified by GC (Lipid Research Centre, Laval University Research Centre (CHUQ)). RBC (300 μl) were thawed and lysed in 1 ml of water. The membranes were then isolated by centrifugation (21 000 g, 15 min) and washed twice with 0·9 % NaCl solution. The pellet was spiked with phosphatidylcholine C:15 (Avanti Polar Lipids, Alabaster, AL, USA) as internal standard. Lipids were extracted with a mixture of chloroform–methanol (2 : 1 v/v) according to a modified Folch method(Reference Shaikh and Downar28). Phospholipid FA were methylated(Reference Lepage and Roy29), and FA profiles were obtained by capillary GC on the temperature gradient of an HP5890 gas chromatograph (Hewlett Packard, Toronto, ON, Canada) equipped with an HP-88 capillary column (100 m × 0·25 mm internal diameter × 0·20 μm film thickness; Agilent Technologies, Santa Clara, CA, USA) coupled with a flame ionization detector. The results are expressed as percentage of total FA. Only n-6 (omega-6) and n-3 PUFA concentrations are reported for the present purpose.
Statistical analysis
Given the small sample size and that most variables had a non-normal distribution, non-parametric tests were preferred. Arithmetic means were also calculated to facilitate comparisons with other studies. Spearman’s partial correlation coefficient was used to determine the correlations between n-3 intakes and RBC concentrations. The Kruskal–Wallis non-parametric ANOVA test was performed to compare RBC FA (% total FA), marine food product (g/d) and EPA + DHA (mg/d) intakes according to tertile of total marine food products intake (g/d). Multiple linear regression analysis was undertaken to determine the relationship between EPA + DHA intake (100 mg/d) and EPA + DHA in RBC (dependent variable). Because elongation of EPA to DHA and retroconversion of DHA to EPA are known mechanisms, EPA + DHA concentration in RBC was preferred as a dependent variable(Reference Sprecher30). Moreover, it has been proposed that EPA + DHA concentration in RBC may be a better independent variable to assess the health effects of n-3 consumption from fish(Reference Harris and Von Schacky31). Covariables were selected without the predictor of interest in the multivariate model and were based on backward selection, considering a liberal P value criterion of 0·5 for all relevant covariates(Reference Babyak32). The final models satisfied collinearity criteria. Statistical analyses were undertaken with the SAS for Windows statistical software package version 9 (SAS Institute, Inc., Cary, NC, USA). Differences between groups and associations were considered significant at P ≤ 0·05 (bilateral).
Results
Baseline characteristics of the study participants are shown in Table 1. As expected, women included in the present validation study had less severe depression, psychological distress and vasomotor symptoms, with better quality of life scores, than those excluded. The other statistically different characteristics in the women included, compared with those excluded, were a higher married/cohabiting rate and superior intakes of total marine food products and EPA + DHA.
Table 1 Baseline characteristics of the study participants: middle-aged women (n 65) who participated in a randomized clinical trial, Québec, Canada
PGWB, Psychological General Well-Being Schedule; PMS, premenstrual syndrome; MDE, major depressive episode.
Intakes of marine food products, EPA and DHA by the study participants are shown in Table 2. Total marine food products intake was 27·6 g/d. EPA, DHA and EPA + DHA intakes were respectively 85·4, 128 and 212 mg/d. Spearman’s correlation coefficient (r s) between EPA, DHA and EPA + DHA intakes and their corresponding concentrations in RBC was significant for total fish and marine food products (Table 3). The oily fish category was the only individual marine group that was significantly correlated. The highest correlations noted were for total marine food products, and the results were 0·46 for RBC EPA, 0·40 for RBC DHA and 0·42 for RBC EPA + DHA. According to the lowest to the highest tertile of total marine food products intake, EPA and DHA content in RBC increased progressively, whereas there were no such correlations for α-LNA and DPA (Table 4). Also, no differences in RBC n-6 were noted according to tertile of total marine food products intake. EPA + DHA intake from oily fish, total fish and marine food products increased across tertile of total marine food products intake. Mean estimated total EPA + DHA intake (mg/d) was 77·0 (sd 47·7) for the first, 174 (sd 83·8) for the second and 379 (sd 154) for the third tertile.
Table 2 Daily intakes of marine food products, EPA and DHA of the study participants: middle-aged women (n 65), Québec, Canada
Table 3 Spearman’s correlation coefficient (r s) between RBC EPA, DHA and EPA + DHA concentrations and their corresponding dietary intakes: middle-aged women (n 65), Québec, Canada
RBC, red blood cell: FA, fatty acids.
Correlation was significant: *P < 0·05.
Table 4 RBC FA concentrations and intakes of marine food products and EPA + DHA according to tertile of total marine food products intake: middle-aged women (n 65), Québec, Canada
RBC, red blood cell; FA, fatty acids; Total n-6, sum of n-6 (18 : 2 + 18 : 3 + 20 : 2 + 20 : 3 + 20 : 4 + 22 : 2 + 22 : 4 + 22 : 5); LA, linoleic acid (18 : 2n-6); AA, arachidonic acid (20 : 4n-6); Total n-3, sum of n-3 (18 : 3 + 18 : 4 + 20 : 3 + 20 : 4 + 20 : 5 + 22 : 5 + 22 : 6); α-LNA, α-linolenic acid (18 : 3n-3); EPA, 20 : 5n-3; DHA, 22 : 6n-3; DPA, docosapentaenoic acid (22 : 5n-3).
†Significance of non-parametric ANOVA, P < 0·05 (Kruskal–Wallis test).
The results of multiple regression analysis of EPA + DHA intake from marine food products v. RBC EPA + DHA concentration are shown in Table 5. Positive and significant correlations were noted for oily fish, total fish and marine food products. No other marine food products significantly predicted EPA + DHA concentration. The contribution of EPA + DHA intake from oily fish, total fish and marine food products to the predicted EPA + DHA concentration was 15 %, 19 % and 21 %, respectively.
Table 5 Linear multiple regression analysis of EPA + DHA intake (100 mg/d) from marine food products and RBC EPA + DHA concentration (% of total FA) as dependent variable: middle-aged women (n 65), Québec, CanadaFootnote †
RBC, red blood cell.
† Models adjusted for age, alcohol, employed outside the home, active, history of major depressive episode, prior hormone therapy, Psychological General Well-Being Schedule score.
‡ Significance of the marine food product.
§ Significance of the general regression model.
Discussion
In the present study, we noted that estimations of EPA + DHA intake from our FFQ were reflected in RBC concentrations. Significant correlations were observed in RBC for oily fish, total fish and marine food products. Multiple linear regression analysis indicated that RBC EPA + DHA concentration increased by 0·42 % with each dietary intake increment of 100 mg EPA + DHA/d.
We discerned that Spearman’s partial correlation coefficients between RBC FA concentrations and their corresponding dietary intakes were 0·46 for EPA, 0·40 for DHA and 0·42 for EPA + DHA. Other studies that evaluated the relationship between RBC concentrations of EPA and DHA and their dietary intakes reported correlation coefficients ranging from 0·21 to 0·55 for EPA and from 0·35 to 0·58 for DHA(Reference Sun, Ma, Campos, Hankinson and Hu12, Reference Godley, Campbell, Miller, Gallagher, Martinson, Mohler and Sandler33–Reference Cao, Schwichtenberg, Hanson and Tsai37). Among 306 women from the Nurses’ Health Survey aged 43–69 years, correlation coefficients between FA intake measured by FFQ in 1990 and RBC FA composition measured in 1990 were 0·38 for EPA and 0·56 for DHA(Reference Sun, Ma, Campos, Hankinson and Hu12). In a cross-sectional analysis of premenopausal (n 93) and postmenopausal (n 104) women aged 39–65 years drawn from the ORDET cohort in Italy, Fuhrman et al. established that correlation coefficients between RBC concentration and dietary FA intake from an FFQ were respectively 0·21 and 0·41 for EPA and 0·43 and 0·44 for DHA(Reference Fuhrman, Barba and Krogh36). Even if correlations between plasma phospholipid and RBC DHA and EPA concentrations are strong(Reference Sun, Ma, Campos, Hankinson and Hu12, Reference Arterburn, Hall and Oken38), it is difficult to directly compare our results with those of studies that used plasma phospholipid measurements. However, it is likely that our correlations might be higher for plasma because our FFQ queries intakes in the last month. Indeed, according to the 18-month controlled study of Katan et al., half maximal and maximal concentrations for EPA in RBC are reached after 28 and 180 d, respectively(Reference Katan, Deslypere, van Birgelen, Penders and Zegwaard39). However, these stages were attained after 4·8 and 56 d for serum cholesteryl esters, indicating that RBC might reflect more long-term intake than plasma or serum.
Except for the oily fish category in our FFQ, we did not observe any significant correlation between RBC EPA + DHA concentration and dietary EPA + DHA contribution of other marine species. The importance of the relationship between EPA + DHA intake from marine species and RBC EPA + DHA concentrations seems to be related to the relative contributions to daily EPA + DHA intakes. Indeed, fatty fish contributed 60 % of the total estimated intake of 212 mg EPA + DHA/d, whereas canned tuna, trout and halibut, and white fish contributed 8 %, 11 % and 7 %, respectively. Among 234 middle-aged Norwegian women, no significant correlation was noted between lean fish intake and serum phospholipid EPA or DHA(Reference Hjartaker, Lund and Bjerve15). In a dietary intervention with enriched n-3 foods (∼125 mg of very LC n-3 PUFA per serving) among overweight volunteers consuming less than 1 serving of fish per week, Patch et al. found that measurement of very LC n-3 PUFA after 6 months reflected habitual intakes(Reference Patch, Murphy and Mansour35). However, no significant correlation was noted among individuals with consumption rates lower than 200 mg/d.
In our study, correlations were slightly superior for EPA compared with DHA. RBC EPA concentration has been suggested to be a better marker of fish and fish oil intake than RBC DHA(Reference Brown, Pang and Roberts40). This might be explained by the fact that EPA measurement in blood appears to be less saturable than DHA(Reference Arterburn, Hall and Oken38, Reference Brown, Pang and Roberts40). Brown et al.(Reference Brown, Pang and Roberts41) suggested that DHA turnover in RBC is slower than that of EPA. However, others have reported stronger correlations between fish intake and plasma DHA than EPA(Reference Woods, Stoney, Ireland, Bailey, Raven, Thien, Walters and Abramson16, Reference Mina, Fritschi and Knuiman17). Nevertheless, it has been postulated that the combination of RBC EPA and DHA may be a better independent variable to assess the health effects of n-3 PUFA consumption from fish(Reference Harris and Von Schacky31). Indeed, RBC EPA + DHA correlates very well with the risk of death from CHD(Reference Harris and Von Schacky31) and n-3 concentration in human myocardial tissue(Reference Harris, Sands, Windsor, Ali, Stevens, Magalski, Porter and Borkon42). Moreover, elongation of EPA to DHA and retroconversion of DHA to EPA are known mechanisms(Reference Sprecher30). Therefore, it is scientifically logical to use EPA + DHA as a biomarker of these FA.
The fact that full diet composition was not estimated by our FFQ represents a major limitation of the present validation study. Indeed, we were unable to evaluate the energy-adjusted effect of EPA/DHA as proposed by Willett(Reference Willett7). We also did not measure the intake of the n-3 PUFA consumed most frequently by North Americans, α-LNA. However, in vivo studies among human subjects with α-LNA tracer showed that 5 % of α-LNA is converted to EPA and <0·5 % to DHA(Reference Plourde and Cunnane11). Therefore, intakes of α-LNA might not interfere in an important way in the relationship between EPA + DHA intakes estimated by the FFQ and RBC EPA + DHA concentrations. The fact that the present FFQ was validated among women only might represent another limitation and constrain external validity. However, conversion of α-LNA to EPA or DHA has been suggested to be higher among young women due to oestrogen(Reference Burdge43). Nevertheless, if this also applies to middle-aged women, higher conversion could have reduced the relationship between RBC EPA + DHA concentration and its dietary intake. Moreover, if the α-LNA conversion rate is likely higher among women than men, the relationship between EPA + DHA intake and RBC EPA + DHA concentration might be at least equal or superior to that in men.
It seems unrealistic to observe a nearly perfect correlation of RBC EPA + DHA concentration with its dietary intake with any food assessment tool. Individuals with similar EPA and DHA intakes may not have similar EPA and DHA concentrations in RBC(Reference Cao, Schwichtenberg, Hanson and Tsai37, Reference Anderson, Solvoll and Drevon44). This might be explained by several factors, such as absorption, tissue turnover, temporal correlation with dietary intake and genes–food–environment interaction(Reference Potischman45). Moreover, the relationship with biomarkers might be biased by many limitations of the dietary assessment tool, such as memory, capacity to describe food, average intake over a period of time, errors in completion and social desirability(Reference Potischman45). In addition, nutrient databases may not adequately reflect temporal changes in food composition(Reference Cantwell8). Even if biomarkers provide more accurate objective measures that are less susceptible to error than dietary intake estimates, measurement errors are possible(Reference Arab5). As suggested by Arab, interpretation of FA concentration (% of total FA) instead of absolute amount (md/dl) might alter the relationship between estimated dietary intake and biomarkers(Reference Arab5). Indeed, all FA are linked when percentages are used. Greater intake of a specific FA might drive down the relative percentage of other FA, even if their intakes are unaltered. Unknown and non-determined disease might also have an effect on FA profiles. In the present study, ill women were excluded, and we restricted our analysis to females without major depression episodes, minor depression and dysthemia.
In conclusion, although the present validation study was conducted among middle-aged women with low consumption of marine food products (<3 servings/week), our simple FFQ provided estimates of EPA and DHA intakes that correlated fairly well with their RBC concentrations.
Acknowledgements
Except M.L., who received speaking honoraria and travel expenses from Isodis Natura, no other author had any financial or conflict of interest related to the present manuscript. The work was supported by the Lucie and André Chagnon Chair for the Teaching of an Integrated Approach in Prevention, Laval University. The omega-3 capsules and matching placebo for the randomized clinical study were provided by Isodis Natura (Brussels, Belgium). The contributions of each author in this work were as follows. Study concept and design: M.L., S.D., C.M., M.-J.P., G.A.; analysis of the data: M.L., S.D., C.M.; interpretation of the data: M.L., S.D., C.M., M.-J.P., G.A.; drafting the manuscript: M.L.; critical revision of the manuscript: M.L., S.D., C.M., M.-J.P., G.A. The authors express their gratitude to all study participants and acknowledge the contributions of their collaborators: Dr G. Roy, Dr Y. Lapierre, Dr T. Chamard-Bergeron, Dr S. Desautels, Dr D. Bélisle, Ms M. Longpré, Ms J. Pelletier, Dr C. Lajeunesse and Ms C. Émond. Trial Registration: International Standard Randomized Controlled Trial Number ISRCTN69617477 (http://www.controlled-trials.com).
Appendix
Fatty acid composition of food products in the Marine Omega-3 Food Frequency Questionnaire (Marine Ω-3 Questionnaire®)†
†Italic numbers represent the mean of EPA and DHA values of each species included in this category. The foods were obtained by an online search for foods in the Canadian Nutrient File, version 2007b (http://www.hc-sc.gc.ca/fn-an/nutrition/fiche-nutri-data/index_e.html; accessed April 2008).
‡Baked or broiled.
§Canned.
||Boiled or steamed.
¶Raw.
