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It should first be emphasized that our aim was not to construct a Food Composition Table for local foodstuffs but, rather, to evaluate the degree of accuracy that can be expected from nutrient-intake data calculated from a Food Composition Table for Use in Latin America (i.e. recommended for this purpose).

It is apparent that differences of up to one order of magnitude can be found between the results of our local analysis and the values for some nutrients given by the INCAP table (the vitamin C content of green pepper determined here was 20 times higher than that given by the table). Of particular interest was the observation that nearly all the values for iron content were below 50 per cent of the value given by the INCAP table. It can readily be appreciated that the use of the table leads to an overestimation of iron consumption, and to reconciling the dietary data with the high prevalence of iron-deficiency anaemia found in the region [2, 11,22]. It is also interesting to note that no value for the iron content of the 20 foodstuffs analysed here fell within 80-120 per cent of the value in the INCAP table. Equally interesting is the fact that the protein content of the so-called "sources of protein" showed little difference between the two values compared here. This might be the starting-point for suggesting that nutrient composition data could be divided into two categories: those of nutrients that show a high variation - probably attributable to regional differences (soil, climate, season, species) - and those of nutrients in some foodstuffs that show very little variation, probably insignificant for dietary evaluation purposes. Minerals and some vitamins are likely examples of the first category, while protein - being a compulsory component of foodstuffs derived from animal or plant tissues - could be a good example of the second category. Appropriate software for identifying the members of each category could be easily developed, and there are probably enough data available from various food composition tables to be used for this purpose.

Table 2. Nutrient composition of local foodstuffs, Recife

  INCAP table no. Moisture Protein Fat Carbohydrate Ash lron Vitamin A Vitamin C
Foodstuff   (%) (%) (%) (%) (%) (mg/100B) (µg/l00g) (mg/l00g)
Pork blood 549 77 17.53 0.12 3.56 1.79 14.70 - 1.31
Pork liver 552 56 26.98 2.30 13.32 1.40 1.40 4,441 40.88
Pork heart 540 68 20.37 3.92 9.58 2.73 14.00 - 5.06
Coriander 143 90 1.10 2.75 3.14 2.99 11.60 1,291 129.00
Green onions 142 89 1.20 3.55 4.63 0.82 0.31 268 47.81
Green pepper 80 92 0.24 3.33 3.60 0.53 0.22 270 190.50
Tomato 271 95 0.49 0.55 2.92 0.65 0.09 368 16.69
Onion 137 85 0.21 2.41 11.57 0.55 0.20 - 11.62
Corn flour 27 11 8.62 1.76 77.54 0.56 0 26  
Beef, lean 579 63 21.93 6.25 7.61 1.12 0.06 - 2.02
Pumpkin 127 68 0.71 0.14 26.45 2.29 0.27 1,526 16.88
Sweet potato 108 64 1.57 0.10 31.02 0.81 0.04 10 26.63
Sweet potato, yellow 107                
Potatoes 242 86 0.71 0.11 11.63 1.27 0.34 0 32.00
Plantain 438 58 1.16 0.59 43.46 1.25 0.30 88 34.03
Cabbage, wild 149 90 4.63 0.17 3.19 1.32 1.44 - 190.69
Cassava flour 276 7 0.52 0.18 88.68 1.14 0.98 - 13.50
Beans, mulatinho 481 13 25.52 1.78 52.38 3.54 4.97 - 2.26
Beef, dried 582 28 56.80 16.32 17.07 15.95 6.90 - 1.13
Bacon 682 7 0.27 80.04 11.05 1.64 - - 1.16
Anguria - 91 1.35 0.05 4.74 0.41 0.34 - 36.38
Okra 252 83 1.61 0.06 12.85 1.21 0.56 14 27.06

Table 3. Estimated iron and vitamin A intakes using nutrient composition figures from INCAP table and analysisa

Nutrient Table Analysis
Protein g/d 20.9 21.7
Iron, mg/d 10.5 3.0
Vitamin A, µg/d    
(as retinol equivalents) 143.2 174.9

a. Food consumption data are from a survey in Agua Preta, Pernambuco [2].

Vitamin A nutriture constitutes a problem that should be looked at - in our region - from another angle. It is apparent that the difference in the figures for consumption resulting from the use of the INCAP table and our results is not enough to explain a lack of prevalence of severe signs of vitamin A deficiency [2, 6, 7, 12] which is not compatible with the very low vitamin A intakes reported in several surveys [2, 9, 12]. One possible explanation might be that some regional fruits, with a very high carotene and carotenoids content, are consumed by the population but not reported in the surveys. We have observed that the fact that some of these fruits are not actually "bought" may lead the population not to consider them as "foods." Thus, a significant contribution to vitamin A intake may have been overlooked in the past.

The problem of regional differences in nutrient composition - and the difficulties generated by the use of food consumption tables which are, most of the time, inadequate for specific situations - is well known. Our data have only shown what the practical implication of this may be, and one way to reconcile dietary data with other indicators of the nutritional status. Our data on "dish-nutrient composition" (fig. 1) shows another very serious drawback in the analysis of survey data with the aid of food composition tables: the so-called "foods-as-eaten" problem. In theory, there has never been any reason to consider as reliable "recipe composition data," i.e. the compound nutrient composition of a dish, obtained by addition of the contribution of each single (raw) ingredient.

Fig. 1. Dish composition: calculated v. analysed values.

This approach ignores liability to heat of a great many nutrients, and losses that may result from chemical reactions as a consequence of the interaction between ingredients which are "incubated" for variable periods at 100°C or more. From a chemical view, feijoada was the dish to undergo the most drastic treatment (see recipe) and, in keeping with this, losses of 66 to 95 per cent were observed for protein and vitamin A respectively, regardless of the nutrient composition value used for the "recipe calculation." It was beyond the scope of this work to determine the actual causes for these losses, and we are first to admit that that of protein was the most intriguing. But the obvious conclusion is that food composition tables cannot continue to be used, without restriction, for calculating nutrient intakes.

The number of foodstuffs and nutrients analysed here was very modest. One should bear in mind, however, that sweet potatoes, cassava flour, sugar, beans, and a little meat account for more than 70 per cent of the daily food intake of the underprivileged in this region [2], as well as in most of the rest of the country. This is what we consider to be "alimentary monotony." Regarding nutrients, our contention is that emphasis should always be given to those capable of generating, by deficient or excessive intake, public health problems. These nutrients would include protein, vitamin A, and iron; the list would vary according to region, but would certainly be limited in each case.

It is becoming increasingly important to count on reliable sources of accurate data for nutrient intake evaluation in connection with a number of nutrition-related diseases.

Our data show that food composition tables do not meet accuracy requirements when the analysis involves foods that are not consumed raw, and where the presence and amount of nutrients in foodstuffs are very dependent on local conditions, mainly soil composition. This work also shows that dietary data can be reconciled with related clinical and biochemical indicators.


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2. M. Batista, N. Chaves, R. M. Varela, M. H. M. Martins, A. C. Salzano, M. O. Bazante, S. M. G. Teixeira, G. J. C. Lima, F. M. Reis, G. C. Martins, and E. R. Linhares, "Inquérito em area urbane da Zona Mata do Nordeste Brasileiro. Agua Preta, Pernambuco," O Hospital, 79: 139-155 (1971).

3. J. P. Church, J. T. Indd, C. W. Young, J. L. Kelsey, and W. W. Kim, "Relationships among Dietary Constituents and Specific Serum Clinical Components of Subjects Eating Self-selected Diets,"A.J.C.N., 40(Suppl.): 1138 1144 (1984).

4. P. V. A. S. Ferro and A. N. Ham, "Colorimetric Determination of Calcium by Chloronilic Acid. 11. A Semimicro Method with Reduced Precipitation Time," Am. J. Clin. Pathol., 28:689 692 (1957).

5. C. H. Fiske and V. Subarow, "The Colorimetric Determination of Phosphorus," J. Biol. Chem., 66: 375 400 (1925).

6. H. Flores, C. R. C. Araujo, F. A. C. S. Campos, and B. Underwood, "Importance of the Early Diagnosis of Vitamin A Deficiency at the Epidemiological Level," Int. J. Vit. Nutr. Res., 24 (Suppl.): 23-34 (1983).

7. H. Flores and C. R. C. Araujo, "Liver Levels of Retinol in Unselected Necropsy Specimens: A Prevalence Survey of Vitamin A Deficiency in Recife, Brazil," A.J.C.N., 40: 146-152 (1984).

8. C. G. Humble, J. M. Samet,. and B. E. Shipper, "The Impact of Revisions in Vitamin A Content Data on Estimates of Nutrient Intake," Nutr. Res., 5: 175 179 (1985).

9. Fundagao Instituto Brasileiro de Geografia e Estatistica (FIBGE), Consumo alimentar: Despesas das famílias: Tabelas seleccionadas (FIBGE, Rio de Janeiro, 1978).

10. Instituto Adolfo Lutz, Normas analíticas do Instituto Adolfo Lutz, vol. 1: Mìtodos químicos e físicos para análise de alimentos (Instituto Adolfo Lutz, Sao Paulo, 1976), pp. 17-29.

11. Interdepartmental Committee on Nutrition for National Development (ICNND), Northeast Brazil; Nutrition Survey, May, 1963 (ICNND, Washington, D.C., 1965).

12. Instituto de Nutriçao da Universidade Federal de Pernambuco (INUFPE), Hipotivaminose A no Brasil (Ministério da Saude/lNAN, Brasilia, 1977).

13. G. L. Kerr, E. S. Less, N. K. M. Lam, R. I. Lorinor, E. Randall, R. N. Forthkofer, M. A. Davis, and S. M. Magnetti, "Relationships between Dietary and Biochemical Measures of Nutritional Status in HANES I Data," A.J. C.N., 35: 294-308 (1982).

14. W. W. Kim, W. Mertz, J. T. Judd, M. W. Marshall, J. L. Kelsay, and E. S. Prather, "Effect of Making Duplicate Food Collections on Nutrient Intakes Calculated from Diet Records," A.J.C.N., 40 (Suppl.): 1333-1337 (l984).

15. C. A. Lang, "The Microdetermination of Kjeldahl Nitrogen in Biological Materials," Anal. Chem., 30: 1692-1694 (1958).

16. R. Lees, Food Analysis: Analytical and Quality Control Methods for Food Manufacturer and Buyer, 3rd ed. (Leonard Hill Books, London, 1975), p. 91.

17. W. T. W. Leung and M. Flores, Tabla de composición de alimentos para uso en America Latina (Instituto de Nutrición de Centroamerica y Panama (INCAP) and Interdepartmental Committee on Nutrition for National Defense (ICNND), Guatemala City, 1961).

18. G. V. Mann, G. Pearson, T. Gordon, and T. R. Dawber, "Diet and Cardiovascular Disease in the Framingham Study," A.J.C.N., 11: 220-225 (1962).

19. M. H. S. Martins and T. Karreco, "Valor nutritivo de alguns pratos regionais," Boletim do Instituto de Nutrição da Universidade Federal de Pernambuco (Recife), 2: 11-129 (1972).

20. C. W. Miles, J. S. Collins, J. T. Holbrook, K. Y. Patterson, and C. E. Bodwell, "Iron Intake and Status of Men and Women Consuming Self-selected Diets," A.J. C. N.,40 (Suppl. ): 1393-1396 (1984).

21. A. A. Rider, B. M. Calkins, R. S. Arthur, and P. P. Nair, "Diet, Nutrition Intake and Metabolism in Populations at High and Low Risk of Colon Cancer. Concordance of Nutrient Information Obtained by Different Methods," A.J.C.N., 40 (Suppl.): 906-913 (1984).

22. A. C. Salzano, M. Batista, H. Flores, and C. L. A. Calado, "Prevalencia de anemia no ciclo gestacional em dois estados do nordeste brasileiro, Pernambuco e Paraiba," Rev. Bras. Pesq. Med. Biol., 13: 211214 (1980).

23. R. Strohecker and H. M. Henning, "Vitamin C Determination," Vitamin Assay (Verlag Chemie, Berlin, 1965), p. 243.

24. A. L. Winton and K. B. Winton, Análisis de alimentos (Ed. Continental, Mexico City, 1957), pp. 75-79.

25. World Health Organization, Vitamin A Deficiency and Xerophthalmia, Technical Report Series, no. 590 (WHO, Geneva, 1976).

The status of food composition data in Asia

Food availability
Generation of food composition data
Users and uses of food composition data
Unmet needs
The future of ASIAFOODS

Institute of Nutrition, Mahidol University, Bangkok, Thailand


The First ASIA FOODS Conference was held from 17 to 21 September 1984 [2]. A total of 22 representatives from 12 Asian countries, as well as 17 resource persons and observers, met in Bangkok to review the current status of food composition data among Asian countries and to discuss the needs to improve food composition data generation, compilation, and use within Asia. An interim executive committee was appointed, with a representative each from Nepal, Sri Lanka, Indonesia, the Philippines, the Republic of Korea, and Japan; Dr. Aree Valyasevi of Thailand was appointed as the chairman of the committee. The executive committee subsequently met in Manila on 18-19 February 1985 [1] to: compile a regional survey of needs relating to food composition data; develop mechanisms for collaboration both within and outside the region; adopt statutes for the ASIA FOODS organization; and develop a five-year action plan' as well as proposals to obtain the assistance required to accomplish the plan.

Because Asia is the largest continent, with a population of over 2 billion, ASIA FOODS has agreed to divide it into three subregions. Those countries invited to participate in the initial ASIA FOODS meeting were distributed among the three subregions as follows:

1. South Asia: Bangladesh, China, India, Nepal, and Sri Lanka.
2. South-East Asia: Brunei, Burma, Indonesia, Malaysia, the Philippines, Singapore, and Thailand.
3. East Asia: Japan, Papua New Guinea, the Republic of Korea, and Taiwan.

These divisions of ASIA FOODS attempt to reflect not only geographical proximity within the Asian continent, but also similarities between the climates, agricultures, and consequently food availability and dietary patterns. By this consolidation into similar subregions, data and analytical methodologies can be shared between the countries of the subregion and ASIA FOODS, resulting in the effective generation, compilation, and dissemination of high-quality food composition data.

Food availability

Considering the size of Asia and the consequent geographical and cultural diversity of the continent, these subdivisions are difficult to make, and all contain compromises with regard to the criteria of categorization employed. None the less, all current members of ASIAFOODS collectively developed this regionalization as a necessary administrative structure, and are satisfied with its arrangement.

With regard to foods produced and consumed within the member countries of ASIAFOODS, there is, of course, tremendous diversity and variety. The range of available species of land and sea animals in addition to the cultivars of fruits and vegetables spanning the region is truly immense. Within each of the regions, however, there are sufficient similarities to allow for the systematic development, utilization, and sharing of necessary methologies.

The national surveys of foods produced, imported, and exported, as reported at the First ASIAFOODS Conference, indicate that the staples for the countries within the region are provided by a wide variety of indigenous cereals and tubers. These are supplemented by the importation of both indigenous and exotic foodstuffs.

For the region as a whole, wheat, maize, rice, dairy products, edible oils, frozen meats, and live animals seem to represent the predominant food imports. Exports consist of many of the imports listed above (excluding wheat and maize), with the addition of freshwater and saltwater fish, shellfish, tropical fruits, spices, coconut, and raw and refined sugar.

The subregion of East Asia leads ASIAFOODS in the production and consumption of processed or "manufactured" foods, and in their importation of the unprocessed agricultural products used in those foods. There is, as yet, no significant exportation from this subregion of either processed or unprocessed foods, although internally there is some international trade in these commodities.

The South-East subregion is characterized largely by the importation of basic food commodities for consumption as dietary staples, along with that of foods that are not widely produced in the region (predominantly dairy products). This is offset by the export of a wide variety of foods, including tropical fruits, seafoods, coconut, and cassava.

The countries of the East and South-East Asia subregions all depend upon rice as the universal staple, with the exception of Papua New Guinea, where the consumption of rice continues to increase. Each of these nations also has a proportionally large seacoast, and so seafoods represent a major part of the available food.

The South Asia subregion would have to be considered a slight net importer of foodstuffs, again with dietary staples being imported and tropical agricultural products - notably fruit, spices, and tea - being exported. Some localities within this subregion suffer from a food deficit, and consequently the inhabitants rely upon wild plants for food on a seasonal or, in some cases, a continual basis. There exist throughout this subregion traditional food processing methods, in addition to rapidly developing modern food-processing technologies; all of these food categories are very much in need of nutrient analysis.

The South Asia subregion contains India and China (both vast countries), which, along with Nepal, Sri Lanka, and Bangladesh, share rice and wheat as the predominant staples. They both contain landlocked localities and areas with ready access to the sea. Although there are local variations, underlying similarities exist throughout China and India, and carry over to the countries adjacent to them.

The diversity of available foods within the ASIAFOODS region is perhaps exceeded only by the region's cultural diversity, which is expressed through the culinary and dietary traditions of the various peoples. Again, it is intended that the subregions capitalize upon the consistencies inherent within each subregion.

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