A Food Frequency Questionnaire for the Assessment of Calcium, Vitamin D and Vitamin K: A Pilot Validation Study

Nutrients 2010, 2, 805-819; doi:10.3390/nu2080805

nutrients

ISSN 2072-6643

www.mdpi.com/journal/nutrients

Article

A Food Frequency Questionnaire for the Assessment of

Calcium, Vitamin D and Vitamin K: A Pilot Validation Study

Janet M. Pritchard

, Tinasha Seechurn

and Stephanie A. Atkinson

Faculty of Health Sciences, McMaster University, 1200 Main St W. Hamilton ON L8N 3Z5,

Canada; E-Mails: [email protected] (J.M.P); ti[email protected]cmaster.ca (T.S.)

Department of Pediatrics, McMaster University, 1200 Main St W. Hamilton ON L8N 3Z5, Canada

* Author to whom correspondence should be addressed; E-Mail: sa[email protected];

Tel.: 905-521-2100, ext 75644; Fax: 905-308-7548.

Received: 9 June 2010; in revised form: 16 July 2010 / Accepted: 17 July 2010 /

Published: 28 July 2010

Abstract: The study objective was to validate a food frequency questionnaire (FFQ) to

assess calcium, vitamin D and vitamin K intakes in overweight and obese postmenopausal

community-dwelling women. The FFQ was validated against intakes derived from a 5-day

diet record (5DDR) that also included assessment of supplement intake. Strong correlations

between methods were observed for all nutrients (r = 0.63, 0.89, 0.54 for calcium, vitamin

D and vitamin K, respectively) and cross-classification analyses demonstrated no major

misclassification of participants into intake quartiles. Bland-Altman analysis showed that

the FFQ overestimated intakes for calcium, by 576 mg/day (95% CI, −668 to 1,821 mg/day),

for vitamin D by 75 IU/day (95% CI, −359 to 510 IU/day), and for

vitamin K by 167 mcg/day (95% CI, −233 to 568 mcg/day). This pilot study showed

promising validation evidence for the use of this FFQ, which focuses on calcium, vitamin

D and vitamin K intakes in postmenopausal women, as a screening tool in clinical

and research settings.

Keywords: osteoporosis; bone; calcium; vitamin D; vitamin K; food frequency

questionnaire; validation

OPEN ACCESS

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1. Introduction

Postmenopausal women are at particular risk of experiencing osteoporosis-related fractures

(i.e., fractures of the hip, wrist, spine) [1]. Such fractures are associated with a significant increase in

morbidity and mortality, and a reduction in quality of life [1-3]. Though the etiologies of osteoporosis

and fractures are multifactorial, calcium, vitamin D and vitamin K intakes through diet and

supplementation have been suggested to impact bone mineral density (BMD), fracture and fall

outcomes [4-10]. However, as reported in a meta-analysis, evidence around the relationship between

bone-nutrient intakes and BMD, fracture and fall outcomes from prospective studies and randomized

controlled trials are not always consistent [11]. Studies are often limited and results heterogeneous as

baseline dietary intakes of calcium, vitamin D and vitamin K are not consistently nor appropriately

assessed in a study population-specific manner.

Nutrient intakes can be estimated through the use of various tools, which differ depending on study

objectives, design and resources. Typically, food frequency questionnaires (FFQ) are used in a clinical

screening setting or in epidemiologic studies to assess dietary intakes, often in relation to the

development of a disease [12]. A thorough review of the utilization of FFQs revealed that randomized

controlled trials, cross-sectional, case-control, and cohort studies have all incorporated FFQ outcome

measures (assessment of food, food groups, or nutrient intakes) into research protocols [12]. The

dietary information derived from FFQs allows researchers to characterize a cohort based on nutrient

intake, examine the relationships between diet and disease, and diet and other study outcome measures,

such as biochemical and functional measures [12-14]. Regardless of the setting or purpose, the

questionnaire should be validated and compared to a gold standard diet analysis technique for the

specific population under study. In particular, it should be country-specific, age-specific and include a

comprehensive list of food items to capture the study population’s eating patterns, food choices and

diet variability [12,15,16].

Previously, an FFQ was developed to estimate a broad range of nutrient intakes in a multicultural

cohort of women living in Southern Ontario, Canada [17]. This FFQ consisted of foods derived from

the Canadian Study of Diet, Lifestyle and Health FFQ food list, and FFQ food-lists specific to

individuals of South Asian, Chinese and European descent living in Canada [17,18]. The FFQ

employed in this study was adapted in style, but revised by focusing on only foods containing

significant amounts of calcium, vitamins D and K from the FFQ that was previously validated,

although not for vitamins D and K [17]. Also, at the time of the initial validation, calcium fortified

foods were not included as they did not exist on the market. Therefore, the objectives of the present

study were to: 1) update the original FFQ with a focus on including an assortment of food items

containing bone-related nutrients; 2) use the improved FFQ in a cohort of postmenopausal women;

3) validate the use of the FFQ to estimate the average intakes of calcium, vitamin D and vitamin K

over a year in postmenopausal women.

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2. Experimental Section

2.1. Participant Recruitment

Individuals who were participating in a larger primary study were approached to participate in the

FFQ validation study. This larger study has been registered at Clinicaltrials.gov and holds the

identifier, NCT00982371. A convenience sample of 15 community-dwelling postmenopausal women

was derived from the larger sample, consisting of 65 participants who resided in Hamilton and

surrounding area in Ontario, Canada. Participant recruitment occurred in-person during a study visit

for the larger study, and over the telephone from January-February 2009. For inclusion into the larger

study, participants must have met the following inclusion criteria: 1) postmenopausal for more than 5

years (menopause was defined as 12 months after the cessation of normal menstrual cycles, in

accordance with the World Health Organization definition); and 2) greater than or equal to 65 years of

age. Exclusion criteria for the primary study were: 1) use of medication in the previous 24 months

known to affect bone, such as hormone therapy, calcitonin, selective estrogen receptor modulator,

fluoride, parathyroid hormone, or bisphosphonate; 2) systemic glucocorticoid use for more than 3

months at a dose of more than 2.5mg/day; 3) history of metastatic cancer (i.e., breast) in the past 5

years; 4) diagnosis of intrinsic bone disease (i.e., Paget’s disease, Cushing’s Syndrome); 5) untreated

malabsorption syndrome (i.e., Celiac disease); 6) self-reported hyperparathyroidism or

hypoparathyroidism; 7) severe renal impairment (Cockcroft-Gault glomerular filtration rate

<30 mL/min). For the FFQ validation study, participants had to be able to record their food and

beverage intake for five non-consecutive days (3 weekdays, 2 weekend days). In addition, participants

completed a questionnaire on current medication use (including dietary supplements), living

arrangements, ambulation status and diagnoses of chronic diseases. All participants signed informed

consent documents. The McMaster University Faculty of Health Sciences/Hamilton Health Sciences

Research Ethics Board reviewed and approved this study.

2.2. Nutrient Analysis

2.2.1. Food Frequency Questionnaire (FFQ)

The interviewer-administered FFQ contained 161 food items that are found to contain ≥30 mg of

calcium, ≥10 IU of vitamin D3, or ≥1 mcg of vitamin K per average serving size. The foods are

arranged into 9 categories based on food grouping (i.e., “dairy/egg products”, “fruits” etc.). For each

food item, participants were asked if the food item is normally consumed at least once a month, and if

so, how often it is consumed (i.e., frequency per day, per week, or per month). The participants were

then asked in what quantity the food-item is consumed (i.e., smaller than average size listed, average

size, or larger than the average size listed). The list of foods included specific items for

calcium/vitamin D-fortified orange juice, cow’s milk and soy beverage. A photograph album was used

as a participant aid while completing the FFQ to assist participants in identifying the food in question

and serving sizes. For assessment of nutritional supplements, specific sections of the FFQ were used to

record vitamin/supplement combinations, including calcium supplements (with seven categories of

amounts), calcium with vitamin D supplements (with eight categories of amounts), vitamin D

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supplements (with six categories of amounts), vitamin K supplements (with eight categories of

amounts), and a section for “other health or nutritional products” not included in the above (e.g.,

calcium-fortified water).

As decided on a priori, only complete FFQs were analyzed. Nutrient intakes were computed using

an in-house FFQ calculator (Microsoft Office Excel 2003, USA). This FFQ calculator is based on the

participant’s frequency of consumption, amount of the item consumed (calculated as 0.5 for smaller

than, and 1.5 for larger than average serving size) and amount of nutrient in the serving size indicated.

Nutrient values for each food item were derived from the 2008 United States Department of

Agriculture (USDA) National Nutrient Database for Standard Reference, the 2007 Health Canada

Canadian Nutrient File (CNF), and from a previously developed FFQ nutrient calculator [17,19,20].

The USDA National Nutrient Database for Standard Reference is the standard reference database

reporting the amount of nutrients in over 7,500 foods commonly consumed in the United States. The

CNF is the standard reference database reporting the amount of nutrients in over 5,500 foods

commonly consumed in Canada. These two open-access databases were used for nutrient analysis

because of the wide variety of frequently updated foods included in each. In addition, the CNF was

used to obtain nutrient information on various bread and cereal products, vegetable oils, margarine, and

dairy products because calcium and vitamin D fortification practices in the USA and Canada differ [21,22].

This ensured that the FFQ in-house calculator contained up-to-date nutrient values for the food items.

2.2.2. 5-Day Diet Record (5DDR)

The 5DDR was selected as the reference method for this validation study because we were

interested in capturing the participant’s habitual eating patterns over 2 weekend days and 3 weekday

days, and to ensure that vitamin K intake was captured [21,22]. Participants were also requested to

indicate how the food item was prepared to provide a more accurate estimation of nutrient intake

(i.e., pan fry with vegetable oil, versus boil with water). The 5DDR was completed by all participants

within one month following the administration of the FFQ. Participants indicated if they took a

calcium, vitamin D, vitamin K or multivitamin supplement, consistent with the FFQ assessment. Of

note, the 5DDRs were not reviewed with the participants upon completion and submission to the

research assistant (TS). Using data from the supplement manufacturer’s website or product labels, the

amount of calcium, vitamin D and vitamin K from the supplement was added to the participant’s

intake. Nutrient intakes were calculated using diet analysis software (Nutritionist Pro, Axxya Systems,

Stafford, Texas USA), which is also based on USDA National Nutrient Database for Standard

Reference and Health Canada’s CNF version 2007b [20,23,24]. All nutrient analysis procedures were

conducted by a single investigator (TS).

2.3. Statistical Analysis

The mean ± SD intakes for each nutrient (calcium, vitamin D, and vitamin K) were calculated.

Frequency statistics were computed for the additional descriptive characteristics. The mean intake

values derived from the FFQ and 5DDR were compared using a paired 2-tailed Student t-test.

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To demonstrate robustness of the validation technique, several statistical methods were utilized. To

determine whether the intakes derived from the FFQ were related to the intakes derived from the

5DDR, Pearson correlation coefficients were used. The Bland-Altman method was used to assess the

agreement between FFQ and 5DDR across a range of nutrient intakes. A cross-classification analysis

was used to determine whether the FFQ and 5DDR have good agreement, or misclassify participants

into categories based on intake levels. In order to perform the cross-classification analysis, the

intakes for calcium, vitamin D and vitamin K derived from the FFQ and 5DDR were divided into

quartiles. The proportions of participants were computed who were classified into the same quartile,

the same ±1 quartile, or who were entirely misclassified after FFQ and 5DDR assessment. To identify

those most at risk of inadequate nutrient intake, the dietary reference intake (DRI) for each nutrient

was used as an intake cut-off. The following cut-off points were used: for calcium, the adequate intake

(AI) of 1,200 mg/day; for vitamin D, the AI of 600 IU/day; and for vitamin K, the AI level of

90 mcg/day [19]. Each subject was classified as having nutrient intake above or below the

corresponding AI. The FFQ sensitivity was defined as the proportion of participants with intake levels

below the AI and the specificity was defined as the proportion of participants with intake levels above

the AI according to results from the FFQ and 5DDR.

Statistical analyses were performed with SPSS (Statistical Package for the Social Sciences) version

15.0 for Windows (SPSS Inc., Chicago, Illinois) and MedCalc Software (Version 10.3, Belgium).

A p-value of <0.05 was considered significant for this study.

3. Results and Discussion

Of the 25 women approached to participate in this study, 5 women declined participation, and 5

women failed to complete and return the 5DDR. Therefore, the results presented here reflect data from

15 women who completed the FFQ and 5DDR. Table 1 displays the demographic characteristics of the

study participants, whose mean age was 70.3 ± 4.7 years. Calcium and vitamin K intakes derived from

the FFQ and 5DDR were significantly different (p < 0.05), but not for vitamin D intakes (Table 2).

However, nutrient intakes derived from the FFQ and 5DDR were positively correlated, with the

strongest correlation between methods for vitamin D intake (Table 2).

Table 1. Descriptive characteristics of participants (N = 15).

Proportion, n (%)

Ethnicity

North-American Caucasian

European

South American

Southeast Asian

11 (73.3)

2 (13.3)

1 (6.7)

Ambulation status

No aid

Walking aid

11 (73.3)

4 (26.7)

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Table 1. Cont.

Living arrangements

Living independently

Living with family support

Living independently with non-live in support

3 (20.0)

9 (60.0)

3 (20.0)

Number of years since menopause

11–15 years

16–20 years

>20 years

3 (20.0)

2 (13.3)

10 (66.7)

Body mass index classification

Normal weight (18.5–24.99 kg/ m

)

Overweight (25–29.99 kg/ m

)

Obese (≥30 kg/ m

)

4 (26.7)

11 (73.3)

Self-reported diagnosis of chronic disease

Osteoporosis

Osteoarthritis

Type 2 diabetes

3 (20.0)

5 (33.3)

12 (80.0)

Number of prescription medications

None

1–5 medications

6–10 medications

11–15 medications

16–20 medications

1 (6.7)

4 (26.7)

1 (6.7)

4 (26.7)

Table 2. Nutrient intakes (mean ± SD) derived from FFQ and 5DDR, and correlation

between methods.

161 item FFQ 5DDR p-

value

Pearso

n r

Diet

sources

Supplement

sources

Total Diet sources Supplement

sources

Total

Calcium

(mg/day)

1,191 ± 671 640 ± 551 1,831 ± 788 615 ± 292 640 ± 551 1,255 ± 492* 0.003 0.63

‡

Vitamin D

(IU/day)

226 ± 156 708 ± 494 934 ± 464 151 ± 209 708 ± 494 859 ± 485 0.253 0.89

‡

Vitamin K

(mcg/day)

266 ± 77 21 ± 51 287 ± 228 99 ± 77 21 ± 51 120 ± 84* 0.009 0.54

‡

*Indicates significant difference between FFQ and 5DDR intakes, p < 0.05. Significant difference between

dietary sources determined by independent samples 2-tailed t-test. ‡ Indicates significant correlation between

FFQ and 5DDR, p < 0.05

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Figure 1. (A) Bland-Altman plots to assess agreement and systematic difference between

the FFQ and 5DDR for calcium intake, (B) vitamin D intake and, (C) vitamin K intake.

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Table 3. Cross-classification analysis to determine proportion of participants classified into

the same, or same ± 1 quartile based on FFQ and 5DDR intakes.

% classified into

same quartile

% classified into

same ± 1 quartile

% misclassified

Calcium

47 87 0

Vitamin D

73 100 0

Vitamin K

33 87 0

For calcium: quartiles 1 to 4 for FFQ were <1,185, 1,185–1,764, 1,765–2,262, >2,262 mg/d; Quartiles 1 to 4

for 5DDR were <841, 841–1,348, 1,349–1,461, >1,461 mg/d; For vitamin D: quartiles 1 to 4 for FFQ were

<561, 561–1,040, 1,041–1,210, >1,210 IU/d; quartiles 1 to 4 for 5DDR were <346, 346–925,

926–1,060, >1,060 IU/d; For vitamin K: quartiles 1 to 4 for FFQ were <135, 135–248, 249–286, >286 mcg/d;

quartiles 1 to 4 for 5DDR were <59, 59–79, 80–150, >150 mcg/d.

4. Discussion and Conclusions

A valid, comprehensive tool to assess the intakes of key bone-nutrients is essential in skeletal health

research involving humans, such as randomized controlled trials, cohort and case-control studies [25,26].

In the present study, we demonstrated that a previously developed 161-item FFQ is valid for the

assessment of calcium, vitamin D and vitamin K intakes in a cohort of overweight and obese

community-dwelling postmenopausal women. In general, the calcium, vitamin D and vitamin K

intakes derived from the FFQ were significantly related to the intakes derived from the 5DDR.

Furthermore, when a participant’s intake was classified into one of four quartiles for each method of

assessment, there were no instances where a participant was misclassified. This FFQ appears to

perform well in a cohort of postmenopausal women, however, it appears to perform best when the

intakes are similar to the adequate intake levels, particularly for calcium and vitamin K [12].

In addition to the FFQ, dietary assessment can be performed using various other tools, which are

associated with their own strengths and weaknesses. While the weighed food record performs well

against an FFQ because portions are weighed prior to consumption, this method may interfere with an

individual’s daily life and habitual dietary intake [12]. The 24-hour recall method is often preferred

over the weighed food record because it is less demanding on a study participant, but tends to rely

more heavily on memory and the ability to conceptualize portion sizes [12]. From a logistical

perspective, an FFQ is an attractive dietary assessment tool for use in health research and some clinical

settings due to the low cost of administration and processing, and low respondent burden. The

additional strengths of this FFQ were its ease of administration, detailed food list, and consideration of

seasonal foods. In southern Ontario, Canada, the consumption of food items varies as the seasons

change from winter to summer. Therefore, by including foods on the FFQ that are consumed on a

seasonal basis (i.e., consumed primarily in the spring and summer, such as broccoli) the opportunity to

capture the participant’s average dietary pattern over several months is improved.

Ease of administration of this FFQ was enhanced by the use of a food photograph album that

emphasized portion sizes. This aid contributed to the interviewer’s ability to complete this FFQ with

the participant in under 25 minutes, which seems to be the average time appropriate for FFQ

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administration [12]. This FFQ contained 161 food items including specific items for calcium and

vitamin D fortified foods, which made the food list longer than other FFQ food lists [24,27]. The

benefits of using an FFQ with a greater number of food items are improved accuracy in food intake

estimates, and improved ability to capture the variability in the population’s diet. A previous study

attempted to shorten an FFQ by reducing the number of food items, however, an adjustment factor had

to be applied to the calcium intake derived from the FFQ due to nutrient intake underestimation [12].

Since it was established that nutrient intake has an effect on bone health, and should be considered

in epidemiological study analyses, researchers have validated FFQs for the assessment of calcium,

vitamin D, vitamin K and other macronutrients [27]. However, ours is the first FFQ to be validated for

the assessment of 3 prominent bone nutrients: calcium; vitamin D; and vitamin K. As noted by

Serra-Majem and colleagues, as the number of validated FFQs increases, certain criteria should be

applied to assess the quality of the validation study. Specifically, the sample and sample size, statistical

analysis, mode of data collection, inclusion of seasonal foods and supplements should be

considered [24,27-35].

Previously, calcium FFQs have been validated for use in Italian [36], Malaysian [33],

Brazilian [29], Vietnamese [35] and general American cohorts [31]. Validating the FFQ for the

specific population under study is essential for improving apparent validity. As age and cognitive

function do not have a significant impact on FFQ validity [27,30,34], we validated the FFQ in older

postmenopausal women, where as others have validated the use of calcium and vitamin D specific FFQs in

younger populations [37,38]. Our study sample was made up of 15 participants, which is a study

limitation. The suggested sample size for an FFQ validation study is 50–100 individuals [27,30,31,34],

however, others have used fewer study participants [12,36] and similar to the present study, produced

promising results. While small in number, our study sample consisted of individuals with varying

levels of independence, as reflected by ambulation status and living arrangements, and chronic disease

diagnoses, which improves the external validity and generalizability of the FFQ to be used in other

study samples consisting of postmenopausal women. It should be noted however that all study

participants were overweight or obese.

The FFQ in the present study overestimated nutrient intakes when compared to the reference

method, which resulted in an overall questionnaire systematic bias, consistent with previous

reports [27,35]. This overestimation could be attributed to: 1) participant awareness of the present

study’s objective to assess bone-related nutrient intakes or the larger study’s objective to assess bone

health; 2) the number of food items in the FFQ [34,35]; 3) or the lack of multiple 5DDR assessments

throughout the year producing an underestimation of intake derived from the reference method [39].

The systematic bias for calcium and vitamin K was more evident for higher intake levels, and less

evident for intake levels around the AI. This suggests that this FFQ would perform the best in

populations where the intake levels were approximately at the AI levels. We speculate that this FFQ

would not perform as well in populations where the intake levels derived from the FFQ were at, or

above the DRI upper limit (UL) levels. The systematic bias for vitamin D was broader, and did not

depend on the proximity to the AI, as seen with calcium and vitamin K, however, the mean difference

between the intakes derived from each method was the smallest for vitamin D (difference of 75 IU/d).

In order to reduce systematic bias, future FFQ validation studies should focus on the use of a

questionnaire, which includes food items aligned with cultural, socio-economic, and geographic

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dietary trends, attempt to keep the participant blinded to the study objectives, and use more than one

reference method data collection time point, if seasonal foods are included in the FFQ food list.

Intakes derived from the FFQ were significantly correlated with intakes derived from the 5DDR.

For calcium the correlation strength was similar to previous that observed in other validation studies [12]

and within the range (0.50–0.70) that is considered suitable for FFQ validation studies [31,34,35]. The

Bland-Altman method of analysis should be used in conjunction with correlation statistics [40]. We

demonstrated that agreement between methods was fairly good for calcium, vitamin D and vitamin K,

with only one (1/15) outlier observation occurring outside the 95% agreement range for each nutrient.

Systematic bias did exist, and the FFQ tended to overestimate nutrient intake, however, it seemed that

for calcium and vitamin K, the agreement between methods was stronger for intakes at approximately

the AI levels. Similar to our findings, Sebring and colleagues also found a systematic bias when

validating a Calcium Questionnaire against 7-day diet records [12].

Finally, we demonstrated that the FFQ was able to place all participants into the same or adjacent

(same ± 1 quartile) quartile of intake for vitamin D intake, and was able to place 87% of participants

into the same or adjacent quartile of intake for calcium and vitamin K. No study participants were

grossly misclassified, which provides evidence that the FFQ performed well when allocating

participants according to dietary intake distribution. These findings are in accordance with the findings

from another validation study in postmenopausal women where approximately 50% of participants

were classified into the same calcium intake quartile with a 60-item FFQ and 3-day diet records [27].

Additional strengths of the present validation study include: 1) the nature of data collection

(i.e., interviewer-administered FFQ); 2) the inclusion of a vast array of seasonal foods containing

calcium and vitamin D and vitamin K and calcium/vitamin D-fortified foods; 3) inclusion of details of

supplement intakes of calcium and vitamins D and K; 4) the reference method chosen. The use of the

5DDR (3 weekdays, 2 weekend days) over the 24-hour recall method is preferred in elderly study

populations because of the 24-hour recall method’s reliance on memory, and problems with

conceptualization of portion sizes, which may distort dietary intake [35]. On average, 4 to 5-day diet

records are appropriate and cost-effective for use as a reference method in FFQ validation studies [41].

This study is not without limitations. First, the generalizability of these findings to the general

population of postmenopausal females and utilisation of the FFQ for future studies must be considered.

The sample size for this study was small, which limits the conclusions we can make and the

generalizability of our findings. This study however provides novel pilot data for future validation

studies in Canadian postmenopausal women, or other cohorts (i.e., older men). Also, the larger study

from which the convenience sample for the present study was drawn excluded individuals who were

on osteoporosis-related therapy, therefore no participants were taking osteoporosis medication. As

previously reported in a large population-based study, approximately 3% and 25% of Canadian women

are on bisphosphonate treatment or hormone therapy, respectively [42].

Furthermore, all participants enrolled in the present study were classified as overweight or obese. It

is possible that the narrow range in BMI measurements of our study participants may influence the

generalizability of our data, as studies have demonstrated that obese women have significantly lower

calcium intakes, compared to non-obese women of the same age, and that lower calcium intake is

associated with insulin resistance, the hallmark of type 2 diabetes [43,44]. It has been reported

however that overweight and obese individuals tend to underreport food consumption in dietary

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assessment studies, which may contribute to the relationship between low calcium intake and

obesity [45,46]. Of note, when compared to total intake levels (dietary and supplementary sources) of

Canadian women over the age of 71 years derived from the 2004 Canadian Community Health Survey

(CCHS) which is based on a 24-hour recall assessment, the present study cohort had similar 5DDR

intake levels of calcium (1,255 ± 492 mg/day, 5DDR vs. 1,638 mg/day, CHHS) [47]. When

Vatanparast and colleagues assessed vitamin D dietary intake levels using the CCHS data, dietary

levels from food sources alone were lower than reported in the present study (859 ± 485 IU/day,

5DDR vs. 244 ± 28 IU/day, CCHS) for all Canadian women over 71 years, however this study

excluded intake levels from supplements [48]. In urban Caucasian Canadian women over 51 years, the

average dietary and supplementary intake of vitamin D was reported to be 544 ± 460 IU/day, which is

comparable to our 5DDR vitamin D estimate [13]. The vitamin K levels reported in this study

(120 ± 84 mcg/day) were also similar to those assessed by a 5DDR in 30 elderly Canadian women and

9 elderly Canadian men, where the mean intake level was 135 ± 154 mcg/day [24].

With respect to the study methodology, the participants were aware of the study objectives, which

may have influenced FFQ responses and 5DDR entries, distorting the habitual intakes of calcium,

vitamin D and vitamin K. Also, only one reference method was used and participants were asked to

complete the 5DDR only once. It has been suggested by others that multiple reference methods,

including dietary methods and biochemical analyses, be used in validation studies [12,36]. If the FFQ

assesses consumption of nutrients over the year (i.e., spanning 4 seasons), multiple time point

collections for the reference method should occur [1]. However, the majority of previous FFQ

validation studies only included one reference method in the analysis [12,36]. Finally, to ensure that

the FFQ is robust for use by different investigators or clinical staff, the inter-rater and intra-rater

reliability should be assessed. This assessment was beyond the scope of the present study, but should

be considered in future FFQ validation studies.

In conclusion, the present study provides promising pilot validation evidence for the use of a “bone

health” FFQ that focuses on calcium, vitamin D and vitamin K in postmenopausal women. Though the

FFQ is not a perfect dietary assessment tool, it can classify individuals into the same or adjacent

quartile of calcium, vitamin D and vitamin K intakes. The FFQ proved to be a sensitive and specific

tool for classifying individuals into calcium and vitamin D adequate intake categories defined by the

Institute of Medicine’s DRI recommendations [27,30,31,34,35]. These findings make this FFQ

particularly attractive for use in a clinical screening setting for nutrient deficiency where resources

may be limited, in a study eligibility screening environment, and in skeletal research involving

postmenopausal women. Future research should aim at validating this FFQ in a larger study

population, and validating this FFQ for use in men and other clinical populations at high risk for

fracture.

Acknowledgements

Special acknowledgements to Susan Docherty-Skippen and Judy Walters for their support

throughout the project, and to the study participants who kindly volunteered their time.

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