Problems In Assessing Dietary Fiber Intakes

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One of the difficulties encountered in making specific recommendations for DF intake is in assessing the current intake levels. Variability in estimated DF intakes can be attributed in part to the type of dietary assessment and method of fiber analysis utilized.

There are three main methods for obtaining dietary data: (1) food balance (e.g. per capita disappearance) statistics; (2) household food surveys; and (3) studies of individuals (42). Dietary data obtained from food balance statistics tend to overestimate actual consumption by individuals (42, 43). Household food survey data need to be corrected for food waste, consumption of meals outside the home, locally grown produce, and household size and composition (42). Studies on individuals, which are probably more representative than the other two techniques, use a variety of methods to assess intake: 24-h recall, food frequency questionnaires, and food records for varying periods which may or may not include weighing of food consumed. Assessments through single 24-h recall tend to underestimate and detailed food records tend to overestimate intake levels (44). The coefficient of variation in day-to-day intake in individuals, which cannot be assessed by 24-h recall, is much greater than intake variability observed season-to-season (44). In comparing a food frequency questionnaire with 7-d weighed records, Saba et al. (45) found that TDF estimates were higher with the questionnaire for all categories of high DF foods. Weighed food records strongly correlate with chemical analysis methods of food composites and independent markers of food intake (i.e. urinary and fecal nitrogen excretion) (46). Thus, the most objec- "S

tive method available is the weighing and recording of all food eaten, but even the act of doing so can disturb a person's normal eating pattern (44).

Most of the fiber databases established in the 1970s were based on CF t?

values. Subsequently, much of the fiber intake data in the 70s and early 80s are derived from the CF method. Bright-See and McKeown-Eyssen reported an estimation of CF and DF (as unavailable CHO) supply in different countries around the world (Table 8) (43). CF estimates drastically underestimate DF values. It should be noted that the DF values reported in this study are much higher than many of the studies cited below because the Southgate method generally reports the highest DF values for high-starch foods and per capita disappearance overestimates nutrient intakes. Marlett and Bokram (47) have tried to establish a relationship between CF and DF which has been used by subsequent studies

Dietary Fiber Intake

Table 8 Estimate of DF Intake in Various Countries Using Unavailable Carbohydrate (CHO) and CF Methods*

Region

Country

CF (g/d)

Unavailable CHO

North America

U.S.

5.9

27.4

Canada

5.4

24.6

Latin America

Costa Rica

8.2

48.3

Cuba

9.1

42.2

Chile

12.8

55.9

Mexico

13.2

93.6

Uruguay

9.3

42.3

Asia-PaciƟc Region

Japan

6.0

31.9

China (Hong Kong)

6.8

35.0

Singapore

7.9

36.6

Australia

4.5

22.8

New Zealand

5.0

24.0

Europe

U.K.

5.0

23.5

Ireland

5.0

26.0

France

5.4

25.3

Italy

7.0

36.1

Portugal

14.7

71.4

Spain

12.5

51.3

Yugoslavia

7.3

45.6

Romania

16

88.1

Hungary

12.3

51.6

Poland

7.5

37.2

Germany

5.6

28.0

Austria

8.9

39.6

Belgium & Luxembourg

5.4

25.9

Bulgaria

16.1

68.1

Czechoslovakia

10.6

45.4

Greece

14.9

62.4

Sweden

4.4

22.1

Switzerland

4.8

23.7

Denmark

5.0

32.5

Finland

4.5

23.1

Netherlands

4.5

22.1

Iceland

5.5

24.2

Norway

8.2

35.3

*Data from ref. #43 based on FAO food disappearance data, 1972-1974 g

Cho et al.

as a conversion factor (48-50). Since the CF level can vary from 10-50% of the TDF value depending on the nature of the food, dietary intake data employing the CF method should be interpreted with caution. Tables of DF levels in foods have been improved by employing AOAC TDF 985.29/991.43, NSP, or unavailable CHO methodology, but limited intake data are available using these new databases.

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