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Rehabilitation Measures Instrument

Dietary History Questionnaire I

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Purpose

The Dietary History Questionnaire I (DHQ I) estimates individuals' dietary intake based on self-reported consumption frequency and portion size of selected foods.

Link to Instrument

Acronym DHQ I

Area of Assessment

Eating
General Health

Assessment Type

Patient Reported Outcomes

Administration Mode

Computer

Cost

Free

Actual Cost

$0.00

Key Descriptions

  • 144 multiple choice questions
  • 124 of the questions measure food consumption
  • Minimum score = 0 for each of the macro and micronutrients
  • No maximal score
  • Questionnaire scored using the free PC software Diet*Calc to generate daily nutrient and food group intake estimates: https://epi.grants.cancer.gov/dhq2/forms/sample/dhq1.2002.data.ncs.report.txt
  • The software comes with another program, “Database Utility” that enables the user or researcher to import the data collected into the Diet*Calc food database

Number of Items

144

Equipment Required

  • Diet*Calc computer software (available at: https://epi.grants.cancer.gov/DHQ/dietcalc/) o Technical support: dhq@imsweb.com
  • Copy of questionnaire

Time to Administer

1-2 hours

Bowman et al, 2011

Required Training

No Training

Age Ranges

Adult

19 +

years

Instrument Reviewers

Initially reviewed by Deborah Hammond MSW, LCSW and Jameelah Williams, OTR/L, CSRS, c/NDT, CPAM in Fall 2018; additional review by Rachel Bond, BA in Fall 2019. 

ICF Domain

Activity

Measurement Domain

General Health

Considerations

  • The DHQ III was released in March 2018, and is only available as a web-based option 
  • Spanish version available in pen and paper, but does not consider ethnic foods
  • The DHQ I may need to be interviewer administered for low literacy populations
  • The DHQ I relies on respondent’s memory and has been shown to be less valid, but more reliable in individuals with mild cognitive impairment (Bowman, 2011)
  • Exclusion of foods popular to ethnic minority groups that are significant contributors of nutrients might skew the dat 

Non-Specific Patient Population

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Normative Data

Healthy adults: (Subar et al., 2001; n = 456 including 202 men; aged 20-70 years; note that sample extracted from DHQ/Willet group as slightly larger sample available)

Nutrient/dietary constituent

Women (n = 254)

Men (n = 202)

Energy (kcal)

1630

2084

Protein (g)

60.8

77.9

Protein (% kcal)

15.4

15.3

Carbohydrate (g)

214.6

257.2

Carbohydrate (% kcal)

52.5

51.3

Fat (g)

56.9

69.3

Fat (% kcal)

32.1

32.6

Saturated fat (g)

18.4

23.3

Monounsaturated fat (g)

21.0

26.9

Polyunsaturated fat (g)

12.5

15.6

Cholesterol (mg)

161

206

Dietary fiber (g)

14.3

17.3

Vitamin A (ug retinol equivalent)

966

973

Vitamin E (mg alpha-tocopherol equivalent)

7.6

9.1

Vitamin C (mg)

106

110

Thiamin (mg)

1.25

1.58

Riboflavin (mg)

1.55

1.88

Niacin (mg)

18.5

24.8

Vitamin B6 (mg)

1.62

1.97

Calcium (mg)

648

765

Iron (mg)

12.2

16.0

Magnesium (mg)

272

339

Phosphorus (mg)

1030

1273

Zinc (mg)

9.0

11.9

Potassium (mg)

2732

3334

Sodium (mg)

2560

3295

Healthy adults: (Subar et al., 2001; n = 430 including 229 women; aged 20-70 years)

Nutrient/dietary constituent

Women (n = 229)

Men (n = 201)

Energy (kcal)

1555

2118

Protein (g)

58.2

80.0

Protein (% kcal)

15.6

15.1

Carbohydrate (g)

202.5

272.6

Carbohydrate (% kcal)

53.5

52.0

Fat (g)

52.2

71.7

Fat (% kcal)

31.4

31.0

Saturated fat (g)

16.7

23.8

Monounsaturated fat (g)

19.4

27.2

Polyunsaturated fat (g)

11.5

14.8

Cholesterol (mg)

106

216

Dietary fiber (g)

14.0

17.1

Vitamin A (ug retinol equivalent)

917

1073

Vitamin E (mg alpha-tocopherol equivalent)

7.2

8.8

Vitamin C (mg)

109

118

Thiamin (mg)

1.21

1.70

Riboflavin (mg)

1.51

2.11

Niacin (mg)

17.5

25.2

Vitamin B6 (mg)

1.54

2.14

Calcium (mg)

635

866

Iron (mg)

12.1

16.0

Magnesium (mg)

250

349

Phosphorus (mg)

1006

1395

Zinc (mg)

8.7

12.2

Potassium (mg)

2644

3437

Sodium (mg)

2460

4382

 

Test/Retest Reliability

Healthy Adults: Individual nutrient correlations with 24 hour recall (Subar et al, 2001 n= 886 including 403 men, age range 20-70)

 

Women

Women

Men

Men

 

Deattenuated correlations (p)

Deattenuated correlations (p) adjusted for energy intake

Deattenuated correlations (p)

Deattenuated correlations (p) adjusted for energy intake

Energy

0.48

--

0.49

--

Protein

0.46

0.60

0.47

0.57

% kcal protein

0.61

--

0.55

--

Carbohydrate

0.50

0.69

0.53

0.63

% kcal carbohydrate

0.69

--

0.68

--

Fat

0.55

0.66

0.52

0.62

% kcal fat

0.67

--

0.66

--

Saturated fat

0.60

0.66

0.57

0.68

Monounsaturated fat

0.56

0.62

0.51

0.60

Polyunsaturated fat

0.48

0.64

0.52

0.61

Cholesterol

0.61

0.66

0.48

0.64

Fiber

0.60

0.77

0.62

0.80

Vitamin A

0.58

0.62

0.60

0.69

Vitamin E

0.43

0.51

0.55

0.57

Vitamin C

0.61

0.68

0.66

0.74

Thiamin

0.54

0.65

0.61

0.83

Riboflavin

0.58

0.66

0.63

0.78

Niacin

0.48

0.64

0.55

0.65

Vitamin B6

0.54

0.65

0.65

0.79

Calcium

0.66

0.73

0.69

0.81

Iron

0.49

0.59

0.59

0.71

Magnesium

0.57

0.78

0.61

0.79

Phosphorus

0.55

0.69

0.58

0.73

Zinc

0.46

0.51

0.42

0.49

Potassium

0.59

0.76

0.58

0.76

Sodium

0.45

0.53

0.36

0.41

Mixed Populations

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Normative Data

Community dwelling African American and Latino Women: (Lee et al, 2011)

 

African-American Females

African American Females

African American Females

Latino Females

Latino Females

Latino Females

Grand Total

Weight Status

Normal

Overweight

Obese

Normal

Overweight

Obese

N/A

Age (years)

37.1 

46.3 

44.1 

41.4 

49.4 

44.37 

Not reported

BMI (km/m2)

18.5-24.9 (n = 24)

25-29.9 (n = 62)

≥ 30 (n = 176)

18.5-24.9 (n = 11)

25-29.9 (n = 33)

≥ 30 (n = 102)

Not reported

Protein (g)

101.5

61.3 

67.4 

43.7 

63.2 

85.6 

72.7 

Carbohydrate(g)

367.3 

202.8

226.6 

162.3 

175.3 

255.5 

230.5 

Dietary Fiber (g)

33.0 

16.9 

17.8 

13.8 

14.1 

20.6 

18.7 

Total Fat (g)

105.8 

65.1 

75.3 

44.2 

66.5 

90.3 

78.2 

Saturated Fat (g)

28.6 

19.7 

22.7 

13.1 

21.7 

29.4 

24.3 

Food Energy (kcal)

2762.0 

1619.3

1836.9 

1236.0 

1542.3 

2158.0 

1898.1

Note: This study included other nutrients reported by the Diet*Cal program; however only the first six are displayed for brevity

 

Test/Retest Reliability

Healthy older adults: (Bowman et al., 2011; n = 19 including 6 males; mean (SD) age = 75 (6) years; retest at 1 month)

  • Excellent reliability for 12/26 (46%) of examined nutrients
  • Adequate reliability for 11/26 (42%) of examined nutrients
  • Poor reliability for 3/26 (12%) of examined nutrients

 

ICC

Alpha-carotene

0.89

Beta-cryptoxanthin

0.89

Beta-carotene

0.88

Lutein + Zeaxanthin

0.86

Lycopene

0.86

Vitamin D

0.85

Vitamin C

0.85

DHA

0.83

Vitamin B12

0.79

EPA

0.78

Total SFA

0.78

Alpha-linolenic acid

0.76

Cholesterol

0.74

Arachidonic  acid

0.70

Selenium

0.66

Folate

0.65

Total MUFA

0.61

Linoleic acid

0.59

Total PUFA

0.57

Gamma-tocopherol

0.56

Iron

0.52

Vitamin B6

0.48

Magnesium

0.41

Copper

0.35

Zinc

0.33

Alpha-tocopherol

0.32

Mild cognitive impairment: (Bowman, et al., 2011); n = 19 including 13 males; mean (SD) age = 73 (9) years; retest at 1 month)

  • Excellent reliability for 25/26 (96%) of examined nutrients
  • Adequate reliability for 1/26 (4%) of examined nutrients

 

ICC

Alpha-carotene

0.77

Beta-cryptoxanthin

0.85

Beta-carotene

0.85

Lutein + Zeaxanthin

0.88

Lycopene

0.88

Vitamin D

0.89

Vitamin C

0.94

DHA

0.86

Vitamin B12

0.8

EPA

0.73

Total SFA

0.93

Alpha-linolenic acid

0.90

Cholesterol

0.91

Arachidonic  acid

0.95

Selenium

0.94

Folate

0.84

Total MUFA

0.95

Linoleic acid

0.95

Total PUFA

0.95

Gamma-tocopherol

0.94

Iron

0.84

Vitamin B6

0.88

Magnesium

0.83

Copper

0.92

Zinc

0.91

Alpha-tocopherol

0.94

Construct Validity

Convergent Validity:

Community dwelling African American and Latino Women: Pearson’s r with DHQ nutrients (Lee et al, 2011; n=410, including 262 African Americans and 148 Latina women)

 

Fruit and Vegetable Screener

Fat Screener

Vegetable and Fruit Log - fruit

Vegetable and Fruit Log - vegetables

Vegetable and Fruit Log - total

Food energy

0.16

0.22

0.08

0.03

0.05

Protein

0.12

0.17

0.12

0.05

0.09

Carbohydrate

0.28

0.05

0.15

0.06

0.11

Daietary fiber

0.32

-0.02

0.28

0.23

0.27

Total fat

0.03

0.32

-0.01

-0.01

-0.01

cholesterol

0.02

0.32

0.02

-0.02

< 0.01

Vegetable servings

0.23

0.08

0.20

0.34

0.30

Fruit servings

0.52

-0.21

0.34

0.22

0.29

Protein % intake

0.01

-0.05

0.14

0.14

0.15

Carbohydrate % intake

0.23

-0.35

0.11

0.01

0.05

Total fat % intake

-0.21

0.31

-0.15

-0.06

-0.11

Cancer

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Criterion Validity (Predictive/Concurrent)

Predictive validity:

Pancreatic cancer: (Thiebaut et al., 2009; n = 525,473 including 308,736 men of which 865 men and  472 women ultimately diagnosed with pancreatic cancer at average follow-up of 6.3 years; average age 51-70 years)

 

Fat Intake

P trend

Hazard Ratio

Total fat from:

Red Meat

0.01

1.06 (1.00 - 1.12)

Dairy Products

< 0.01

1.07 (1.01 - 1.12)

Animal Food Sources

< 0.001

1.23 (1.11 - 1.36)

Vegetable Food Source

0.83

1.00 (0.91 - 1.09)

Saturated fat from:

Red Meat

0.02

1.06 (1.00 - 1.12)

Dairy Products

< 0.01

1.06 (1.01 - 1.12)

Animal Food Sources

< 0.001

1.19 (1.09 - 1.30)

Vegetable Food Sources

0.94

1.02 (0.94 - 1.11)

Monosaturated fat from:

Red Meat

0.02

1.06 (1.00 - 1.12)

Dairy Products

< 0.01

1.07 (1.01 - 1.12)

Animal Food Sources

< 0.001

1.22 (1.11 - 1.35)

Vegetable Food Source

0.74

0.97 (0.90 - 1.05)

Energy adjusted regression model for pancreatic cancer risk by food source

 

Bibliography

Bowman, G. L., Shannon, J., Ho, E., Traber, M. G., Frei, B., Oken, B. S., … Quinn, J. F. (2011). “Reliability and validity of food frequency questionnaire and nutrient biomarkers in elders with and without mild cognitive impairment”. Alzheimer Disease and Associated Disorders, 25(1), 49–57. https://doi.org/

Kipnis, V., Subar, A.F., Midthune, D., Freedman, L.S., Ballard-Barbash, R., Trolano, R., Bingham, S., Schoeller, D, A., Schatzkin, A., Carroll, R. (2003). “Structure of Dietary Measurement of Error: Results of the OPEN Biomarker Study.” American Journal of Epidemiology.158(1): 14-21

Lee,R.E., Mama, S.K., Medina.A.V., Reese-Smith, J.Y., Banda, J.A., Layne, C.S., Baxter,M. O’Connor, D.P., McNeil,L., Estabrooks,P., (2001).”Multiple Measures of Physical Activity, Dietary Habits and Weight Status in African American and Hispanic or Latina Women.”  Journal of Community Health. 36(6): 1011-1023.

Subar, A. F., Thompson, F. E., Kipnis, V., Midthune, D., Hurwitz, P., McNutt, S., McIntosh, A., Rosenthal, S, (2001). “Comparative Validation of the Block, Willett, and National Cancer Institute Food Frequency Questionnaires.” American Journal of Epidemiology .154(12): 1089-1099.

Thiébaut, A. C. M., Jiao, L., Silverman, D. T., Cross, A. J., Thompson, F. E., Subar, A. F., … Stolzenberg-Solomon, R. Z. (2009). “Dietary fatty acids and pancreatic cancer in the NIH-AARP diet and health study”. Journal of the National Cancer Institute, 101(14), 1001–1011. https://doi.org/10.1093/jnci/djp168

Thompson, F.E., Subar, A.F., Brown, C.C., Smith, A. F., Sharbaugh, C.O., Jobe, J.B., Mitti, B., Gibson, J.T., Ziegler, R. G., (2002). “Cognitive Research enhances accuracy of food frequency questionnaire reports: Results of an experimental validation study.”  Journal of American Diet Association. 102(2): 212-25.